Thursday, 14 March 2019

2019 Call for CIS Award Nominations

The IEEE Computational Intelligence Society annually recognizes significant contributions and meritorious service in the field of computational intelligence. Recognizing volunteers and eminent colleagues is a key element to keep our Society alive and to promote research excellence in computational intelligence.

Please consider nominating well deserving colleagues for one of the following awards:

  • Neural Networks Pioneer Award
  • Fuzzy Systems Pioneer Award
  • Evolutionary Computation Pioneer Award
  • Meritorious Service Award
  • IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Award
  • Outstanding Chapter Award
  • Outstanding Ph.D. Dissertation Award
  • Outstanding Organization Award
  • Outstanding Early Career Award
The completed nomination must be submitted by email to the Awards Soliciting Nominations Subcommittee Chair Prof. Sanaz Mostaghim at and a copy to by 30 April 2019 in a single, standalone pdf file. The nomination can be considered submitted only after acknowledgement of the Awards Soliciting Nominations Subcommittee Chair.

The nominations deadline is strict.

For the following publications, all papers published in 2017 will be evaluated and considered for the award:
  • IEEE Transactions on Fuzzy Systems Outstanding Paper Award
  • IEEE Transactions on Evolutionary Computation Outstanding Paper Award
  • IEEE Transactions on Cognitive and Development Systems Outstanding Paper Award
  • IEEE Transactions on Computational Intelligence and AI in Games Outstanding Paper Award (title changed in 2018 to IEEE Transactions on Games for future awards)
  • IEEE Computational Intelligence Magazine.

For more information, details and procedural aspects, please visit the awards website or contact the CIS Awards Committee Chair, Prof. Cesare Alippi at

Wednesday, 13 March 2019

CFP: The Third International Conference on Intelligent Computing in Data Sciences (ICDS 2019)

The Third International Conference on Intelligent Computing in Data Sciences (ICDS 2019)
October 28-30, 2019 Marrakech, Morocco

IEEE Conference Record Number : #47004

ICDS2019 is technically Co-Sponsored by IEEE Computational Intelligence Society and the International Neural Network Society (INNS).

Conference Proceedings Citation Index: IEEE Xplore Digital Library (ISBN : 978-1-7281-0003-6) and Scopus.

Conference Website:

Conference Topics:
1. Intelligent Computing
  • Computational Intelligence
  • Neural Networks theory and models
  • Fuzzy systems
  • Evolutionary algorithms
  • Cognitive science and Connectionist theory
  • Deep learning
  • Reinforcement Learning
  • Ambient Intelligence
  • Big data analytics, visualization, modeling
  • Brain imaging and neural information processing
  • Machine Learning
  • Agent Based Systems and collective intelligence
  • Expert Systems

2. Areas and Applications include but not limited to:
  • Machine Learning Algorithms for high-velocity Streaming data
  • Data Mining, Text mining & web mining
  • Natural language processing
  • Neurorobotics and Intelligent Robotics
  • Image/Video Processing
  • Health care
  • Speech Processing
  • Intelligent Transportation Systems
  • Data pre-processing, sampling and reduction
  • High performance computing for data analytics
  • Smart grid
  • Sensor Networks and Security
  • Bioinformatics
  • Intrusion detection and fault diagnosis

Important dates:
  • Paper Submission deadline : April 30, 2019
  • Notification of acceptance : June 20, 2019
  • Camera-ready : June 30, 2019
  • Conference date : October 28-29-30, 2019

Saturday, 2 March 2019

Call for IEEE TNNLS Outstanding Paper Award Nomination

We are accepting nominations for the IEEE TNNLS Outstanding Paper Award, a prestigious award in recognizing outstanding papers published in TNNLS. Here are the important information:

1. For the current round of competition, any paper published in 2017 (Volume 28) of TNNLS is eligible for consideration.

2. The nomination deadline is April 30, 2019 (strict deadline).

3. The complete nomination packet must include the following information: Nominator, Full Citation of the Nominated Paper (including author names, paper title, publication volume, issue, and page numbers), Basis for Nomination, Proposed Citation, 3 Reference Letters, and a Copy of the Nominated Paper.

4. The complete nomination package should be submitted in a single PDF file by email to the Awards Soliciting Nominations Subcommittee Chair, Prof. Sanaz Mostaghim at and a copy to and

The nomination cannot be considered complete until the submitted package is acknowledged by the Chair of the Awards Soliciting Nominations Subcommittee.

IEEE Transactions on Neural Networks and Learning Systems, Volume 30, Issue 3, March 2019

1. NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Author(s): Alessandro Aimar; Hesham Mostafa; Enrico Calabrese; Antonio Rios-Navarro; Ricardo Tapiador-Morales; Iulia-Alexandra Lungu; Moritz B. Milde; Federico Corradi; Alejandro Linares-Barranco; Shih-Chii Liu; Tobi Delbruck
Pages: 644 - 656

2. Robust Dimension Reduction for Clustering With Local Adaptive Learning
Author(s): Xiao-Dong Wang; Rung-Ching Chen; Zhi-Qiang Zeng; Chao-Qun Hong; Fei Yan
Pages: 657 - 669

3. Learning of a Decision-Maker’s Preference Zone With an Evolutionary Approach
Author(s): Manish Aggarwal
Pages: 670 - 682

4. Fine-Grained Image Classification Using Modified DCNNs Trained by Cascaded Softmax and Generalized Large-Margin Losses
Author(s): Weiwei Shi; Yihong Gong; Xiaoyu Tao; De Cheng; Nanning Zheng
Pages: 683 - 694

5. Distributed Generalized Nash Equilibrium Seeking Algorithm Design for Aggregative Games Over Weight-Balanced Digraphs
Author(s): Zhenhua Deng; Xiaohong Nian
Pages: 695 - 706

6. DBSDA: Lowering the Bound of Misclassification Rate for Sparse Linear Discriminant Analysis via Model Debiasing
Author(s): Haoyi Xiong; Wei Cheng; Jiang Bian; Wenqing Hu; Zeyi Sun; Zhishan Guo
Pages: 707 - 717

7. Modulation Classification Based on Signal Constellation Diagrams and Deep Learning
Author(s): Shengliang Peng; Hanyu Jiang; Huaxia Wang; Hathal Alwageed; Yu Zhou; Marjan Mazrouei Sebdani; Yu-Dong Yao
Pages: 718 - 727

8. ICFS Clustering With Multiple Representatives for Large Data
Author(s): Liang Zhao; Zhikui Chen; Yi Yang; Liang Zou; Z. Jane Wang
Pages: 728 - 738

9. Exponential Stabilization of Fuzzy Memristive Neural Networks With Hybrid Unbounded Time-Varying Delays
Author(s): Yin Sheng; Frank L. Lewis; Zhigang Zeng
Pages: 739 - 750

10. A Fused CP Factorization Method for Incomplete Tensors
Author(s): Yuankai Wu; Huachun Tan; Yong Li; Jian Zhang; Xiaoxuan Chen
Pages: 751 - 764

11. Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure
Author(s): Fanghui Liu; Xiaolin Huang; Chen Gong; Jie Yang; Johan A. K. Suykens
Pages: 765 - 776

12. Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives
Author(s): Chenguang Yang; Chuize Chen; Wei He; Rongxin Cui; Zhijun Li
Pages: 777 - 787

13. Discriminative Feature Selection via Employing Smooth and Robust Hinge Loss
Author(s): Hanyang Peng; Cheng-Lin Liu
Pages: 788 - 802

14. A Fast and Accurate Matrix Completion Method Based on QR Decomposition and L2,1 Norm Minimization
Author(s): Qing Liu; Franck Davoine; Jian Yang; Ying Cui; Zhong Jin; Fei Han
Pages: 803 - 817

15. Local Restricted Convolutional Neural Network for Change Detection in Polarimetric SAR Images
Author(s): Fang Liu; Licheng Jiao; Xu Tang; Shuyuan Yang; Wenping Ma; Biao Hou
Pages: 818 - 833

16. Cost-Effective Object Detection: Active Sample Mining With Switchable Selection Criteria
Author(s): Keze Wang; Liang Lin; Xiaopeng Yan; Ziliang Chen; Dongyu Zhang; Lei Zhang
Pages: 834 - 850

17. Multiview Subspace Clustering via Tensorial t-Product Representation
Author(s): Ming Yin; Junbin Gao; Shengli Xie; Yi Guo
Pages: 851 - 864

18. Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network
Author(s): Junxiu Liu; Liam J. Mcdaid; Jim Harkin; Shvan Karim; Anju P. Johnson; Alan G. Millard; James Hilder; David M. Halliday; Andy M. Tyrrell; Jon Timmis
Pages: 865 - 875

19. Fast and Accurate Hierarchical Clustering Based on Growing Multilayer Topology Training
Author(s): Yiu-ming Cheung; Yiqun Zhang
Pages: 876 - 890

20. General Square-Pattern Discretization Formulas via Second-Order Derivative Elimination for Zeroing Neural Network Illustrated by Future Optimization
Author(s): Jian Li; Yunong Zhang; Mingzhi Mao
Pages: 891 - 901

21. Optimal Control of Propagating Fronts by Using Level Set Methods and Neural Approximations
Author(s): Angelo Alessandri; Patrizia Bagnerini; Mauro Gaggero
Pages: 902 - 912

22. Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
Author(s): Ramasamy Saravanakumar; Hyung Soo Kang; Choon Ki Ahn; Xiaojie Su; Hamid Reza Karimi
Pages: 913 - 922

23. Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures
Author(s): Mohammadreza Mohaghegh Neyshabouri; Kaan Gokcesu; Hakan Gokcesu; Huseyin Ozkan; Suleyman Serdar Kozat
Pages: 923 - 937

24. Adaptive Optimal Output Regulation of Time-Delay Systems via Measurement Feedback
Author(s): Weinan Gao; Zhong-Ping Jiang
Pages: 938 - 945

25. Unsupervised Knowledge Transfer Using Similarity Embeddings
Author(s): Nikolaos Passalis; Anastasios Tefas
Pages: 946 - 950

26. Synchronization of Coupled Markovian Reaction–Diffusion Neural Networks With Proportional Delays Via Quantized Control
Author(s): Xinsong Yang; Qiang Song; Jinde Cao; Jianquan Lu
Pages: 951 - 958

27. Stepsize Range and Optimal Value for Taylor–Zhang Discretization Formula Applied to Zeroing Neurodynamics Illustrated via Future Equality-Constrained Quadratic Programming
Author(s): Yunong Zhang; Huihui Gong; Min Yang; Jian Li; Xuyun Yang
Pages: 959 - 966

Tuesday, 26 February 2019

2019 Graduate Student Research Grants - Call for Applications

The deadline for applications for scholarships for undergraduate, graduate and PhD students to carry out research during an academic break period is 15 March 2019. The scholarships can cover expenses related to a visit to another university, institute or research agency for collaboration with an identified researcher in the applicant's field of interest.The research field should be connected with the CIS (neural networks, fuzzy systems, or evolutionary computation). More information can be found here:

IEEE Transactions on Fuzzy Systems, Volume 27, Issue 1, Jan. 2019

1) A Nested Tensor Product Model Transformation
Author(s): Y Yu, Z Li, X Liu, K Hirota, X Chen, T Fernando, H H C Lu
Pages: 1 - 15

2) High-order Intuitionistic Fuzzy Cognitive Map Based on Evidential Reasoning Theory
Author(s): Y Zhang, J Qin, P Shi, Y Kang
Pages: 16 - 30

3) Joint Learning of Spectral Clustering Structure and Fuzzy Similarity Matrix of Data
Author(s): Z Bian, H Ishibuchi, S Wang
Pages: 31 - 44

4) Fuzzy Optimal Energy Management for Fuel Cell and Supercapacitor Systems Using Neural Network Based Driving Pattern Recognition
Author(s): R Zhang, J Tao, H Zhou
Pages: 45 - 57

5) Comparing the Performance Potentials of Interval and General Type-2 Rule-Based Fuzzy Systems in Terms of Sculpting the State Space
Author(s): J M Mendel
Pages: 58 - 71

6) LDS-FCM: A Linear Dynamical System Based Fuzzy C-Means Method for Tactile Recognition
Author(s): C Liu, W Huang, F Sun, M Luo, C Tan
Pages: 72 - 83

7) Improving Risk Evaluation in FMEA With Cloud Model and Hierarchical TOPSIS Method
Author(s): H-C Liu, L-E Wang, Z-W Li, Y-P Hu
Pages: 84 - 95

8) Finite-Time Adaptive Fuzzy Output Feedback Dynamic Surface Control for MIMO Nonstrict Feedback Systems
Author(s): Y Li, K Li, S Tong
Pages: 96 - 110

9) BPEC: Belief-Peaks Evidential Clustering
Author(s): Z-G Su, T Denoeux
Pages: 111 - 123

10) Improving the Performance of Fuzzy Rule-Based Classification Systems Based on a Nonaveraging Generalization of CC-Integrals NamedCF1F2-Integrals
Author(s): G Lucca, G P Dimuro, J Fernandez, H Bustince, B Bedregal, J A Sanz
Pages: 124 - 134

11) The Negation of a Basic Probability Assignment
Author(s): L Yin, X Deng, Y Deng
Pages: 135 - 143

12) Event Triggered Adaptive Fuzzy Consensus for Interconnected Switched Multiagent Systems
Author(s): S Zheng, P Shi, S Wang, Y Shi
Pages: 144 - 158

13) Alternative Ranking-Based Clustering and Reliability Index-Based Consensus Reaching Process for Hesitant Fuzzy Large Scale Group Decision Making
Author(s): X Liu, Y Xu, R Montes, R-X Ding, F Herrera
Pages: 159 - 171

14) Fuzzy Adaptive Finite-Time Control Design for Nontriangular Stochastic Nonlinear Systems
Author(s): S Sui, C L P Chen, S Tong
Pages: 172 - 184

15) Deviation-Sparse Fuzzy C-Means With Neighbor Information Constraint
Author(s): Y Zhang, X Bai, R Fan, Z Wang
Pages: 185 - 199

16) Sampled-Data Adaptive Output Feedback Fuzzy Stabilization for Switched Nonlinear Systems With Asynchronous Switching
Author(s): S Li, C K Ahn, Z Xiang
Pages: 200 - 205

Saturday, 23 February 2019

IEEE Transactions on Neural Networks and Learning Systems: Volume 30, Issue 1, January 2019

1. Editorial: Booming of Neural Networks and Learning Systems
Page(s): 2 - 10

2. Deep CNN-Based Blind Image Quality Predictor
Author(s): Jongyoo Kim; Anh-Duc Nguyen; Sanghoon Lee
Page(s): 11 - 24

3. Neuro-Adaptive Control With Given Performance Specifications for Strict Feedback Systems Under Full-State Constraints
Author(s): Xiucai Huang; Yongduan Song; Junfeng Lai
Page(s): 25 - 34

4. Consensus Problems Over Cooperation-Competition Random Switching Networks With Noisy Channels
Author(s): Yonghong Wu; Bin Hu; Zhi-Hong Guan
Page(s): 35 - 43

5. Estimation of Graphlet Counts in Massive Networks
Author(s): Ryan A. Rossi; Rong Zhou; Nesreen K. Ahmed
Page(s): 44 - 57

6. Finite-Time Passivity-Based Stability Criteria for Delayed Discrete-Time Neural Networks via New Weighted Summation Inequalities
Author(s): Ramasamy Saravanakumar; Sreten B. Stojanovic; Damnjan D. Radosavljevic; Choon Ki Ahn; Hamid Reza Karimi
Page(s): 58 - 71

7. Multiple-Model Adaptive Estimation for 3-D and 4-D Signals: A Widely Linear Quaternion Approach
Author(s): Min Xiang; Bruno Scalzo Dees; Danilo P. Mandic
Page(s): 72 - 84

8. Optimal Synchronization Control of Multiagent Systems With Input Saturation via Off-Policy Reinforcement Learning
Author(s): Jiahu Qin; Man Li; Yang Shi; Qichao Ma; Wei Xing Zheng
Page(s): 85 - 96

9. Design and Adaptive Control for an Upper Limb Robotic Exoskeleton in Presence of Input Saturation
Author(s): Wei He; Zhijun Li; Yiting Dong; Ting Zhao
Page(s): 97 - 108

10. A Cost-Sensitive Deep Belief Network for Imbalanced Classification
Author(s): Chong Zhang; Kay Chen Tan; Haizhou Li; Geok Soon Hong
Page(s): 109 - 122

11. A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons
Author(s): Malu Zhang; Hong Qu; Ammar Belatreche; Yi Chen; Zhang Yi
Page(s): 123 - 137

12. Enhanced Robot Speech Recognition Using Biomimetic Binaural Sound Source Localization
Author(s): Jorge Dávila-Chacón; Jindong Liu; Stefan Wermter
Page(s): 138 - 150

13. A Discrete-Time Projection Neural Network for Sparse Signal Reconstruction With Application to Face Recognition
Author(s): Bingrong Xu; Qingshan Liu; Tingwen Huang
Page(s): 151 - 162

14. Domain-Weighted Majority Voting for Crowdsourcing
Author(s): Dapeng Tao; Jun Cheng; Zhengtao Yu; Kun Yue; Lizhen Wang
Page(s): 163 - 174

15. Reconstructible Nonlinear Dimensionality Reduction via Joint Dictionary Learning
Author(s): Xian Wei; Hao Shen; Yuanxiang Li; Xuan Tang; Fengxiang Wang; Martin Kleinsteuber; Yi Lu Murphey
Page(s): 175 - 189

16. On the Duality Between Belief Networks and Feed-Forward Neural Networks
Author(s): Paul M. Baggenstoss
Page(s): 190 - 200

17. Exploiting Combination Effect for Unsupervised Feature Selection by L2,0 Norm
Author(s): Xingzhong Du; Feiping Nie; Weiqing Wang; Yi Yang; Xiaofang Zhou
Page(s): 201 - 214

18. Leader-Following Practical Cluster Synchronization for Networks of Generic Linear Systems: An Event-Based Approach
Author(s): Jiahu Qin; Weiming Fu; Yang Shi; Huijun Gao; Yu Kang
Page(s): 215 - 224

19. Semisupervised Learning Based on a Novel Iterative Optimization Model for Saliency Detection
Author(s): Shuwei Huo; Yuan Zhou; Wei Xiang; Sun-Yuan Kung
Page(s): 225 - 241

20. Augmented Real-Valued Time-Delay Neural Network for Compensation of Distortions and Impairments in Wireless Transmitters
Author(s): Dongming Wang; Mohsin Aziz; Mohamed Helaoui; Fadhel M. Ghannouchi
Page(s): 242 - 254

21. UCFTS: A Unilateral Coupling Finite-Time Synchronization Scheme for Complex Networks
Author(s): Min Han; Meng Zhang; Tie Qiu; Meiling Xu
Page(s): 255 - 268

22. A Semisupervised Classification Approach for Multidomain Networks With Domain Selection
Author(s): Chuan Chen; Jingxue Xin; Yong Wang; Luonan Chen; Michael K. Ng
Page(s): 269 - 283

23. Neurons With Paraboloid Decision Boundaries for Improved Neural Network Classification Performance
Author(s): Nikolaos Tsapanos; Anastasios Tefas; Nikolaos Nikolaidis; Ioannis Pitas
Page(s): 284 - 294

24. Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems With Unknown Nonaffine Dead-Zone Input
Author(s): Yan-Jun Liu; Shu Li; Shaocheng Tong; C. L. Philip Chen
Page(s): 295 - 305

25. Filippov Hindmarsh–Rose Neuronal Model With Threshold Policy Control
Author(s): Yi Yang; Xiaofeng Liao
Page(s): 306 - 311

26. Blind Denoising Autoencoder
Author(s): Angshul Majumdar
Page(s): 312 - 317

27. Variational Random Function Model for Network Modeling
Author(s): Zenglin Xu; Bin Liu; Shandian Zhe; Haoli Bai; Zihan Wang; Jennifer Neville
Page(s): 318 - 324

IEEE Transactions on Neural Networks and Learning Systems: Volume 30, Issue 2, February 2019.

1. fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs
Author(s): Stylianos I. Venieris; Christos-Savvas Bouganis
Page(s): 326 - 342

2. A Novel Neural Networks Ensemble Approach for Modeling Electrochemical Cells
Author(s): Massimiliano Luzi; Maurizio Paschero; Antonello Rizzi; Enrico Maiorino; Fabio Massimo Frattale Mascioli
Page(s): 343 - 354

3. Exploring Correlations Among Tasks, Clusters, and Features for Multitask Clustering
Author(s): Wenming Cao; Si Wu; Zhiwen Yu; Hau-San Wong
Page(s): 355 - 368

4. Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach
Author(s): Liang Lan; Zhuang Wang; Shandian Zhe; Wei Cheng; Jun Wang; Kai Zhang
Page(s): 369 - 378

5. Optimized Neural Network Parameters Using Stochastic Fractal Technique to Compensate Kalman Filter for Power System-Tracking-State Estimation
Author(s): Hossam Mosbah; Mohamed E. El-Hawary
Page(s): 379 - 388

6. Online Identification of Nonlinear Stochastic Spatiotemporal System With Multiplicative Noise by Robust Optimal Control-Based Kernel Learning Method
Author(s): Hanwen Ning; Guangyan Qing; Tianhai Tian; Xingjian Jing
Page(s): 389 - 404

7. Semisupervised Learning With Parameter-Free Similarity of Label and Side Information
Author(s): Rui Zhang; Feiping Nie; Xuelong Li
Page(s): 405 - 414

8. H-infinity State Estimation for Discrete-Time Nonlinear Singularly Perturbed Complex Networks Under the Round-Robin Protocol
Author(s): Xiongbo Wan; Zidong Wang; Min Wu; Xiaohui Liu
Page(s): 415 - 426

9. Temporal Self-Organization: A Reaction–Diffusion Framework for Spatiotemporal Memories
Author(s): Prayag Gowgi; Shayan Srinivasa Garani
Page(s): 427 - 448

10. Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling
Author(s): Zhanyu Ma; Yuping Lai; W. Bastiaan Kleijn; Yi-Zhe Song; Liang Wang; Jun Guo
Page(s): 449 - 463

11. Hierarchical Decision and Control for Continuous Multitarget Problem: Policy Evaluation With Action Delay
Author(s): Jiangcheng Zhu; Jun Zhu; Zhepei Wang; Shan Guo; Chao Xu
Page(s): 464 - 473

12. Unified Low-Rank Matrix Estimate via Penalized Matrix Least Squares Approximation
Author(s): Xiangyu Chang; Yan Zhong; Yao Wang; Shaobo Lin
Page(s): 474 - 485

13. Online Active Learning Ensemble Framework for Drifted Data Streams
Author(s): Jicheng Shan; Hang Zhang; Weike Liu; Qingbao Liu
Page(s): 486 - 498

14. A New Approach to Stochastic Stability of Markovian Neural Networks With Generalized Transition Rates
Author(s): Ruimei Zhang; Deqiang Zeng; Ju H. Park; Yajuan Liu; Shouming Zhong
Page(s): 499 - 510

15. Optimization of Distributions Differences for Classification
Author(s): Mohammad Reza Bonyadi; Quang M. Tieng; David C. Reutens
Page(s): 511 - 523

16. Deep Convolutional Identifier for Dynamic Modeling and Adaptive Control of Unmanned Helicopter
Author(s): Yu Kang; Shaofeng Chen; Xuefeng Wang; Yang Cao
Page(s): 524 - 538

17. Neural-Response-Based Extreme Learning Machine for Image Classification
Author(s): Hongfeng Li; Hongkai Zhao; Hong Li
Page(s): 539 - 552

18. Deep Ensemble Machine for Video Classification
Author(s): Jiewan Zheng; Xianbin Cao; Baochang Zhang; Xiantong Zhen; Xiangbo Su
Page(s): 553 - 565

19. Multiple ψ-Type Stability of Cohen–Grossberg Neural Networks With Both Time-Varying Discrete Delays and Distributed Delays
Author(s): Fanghai Zhang; Zhigang Zeng
Page(s): 566 - 579

20. Neural Network Training With Levenberg–Marquardt and Adaptable Weight Compression
Author(s): James S. Smith; Bo Wu; Bogdan M. Wilamowski
Page(s): 580 - 587

21. Solving Partial Least Squares Regression via Manifold Optimization Approaches
Author(s): Haoran Chen; Yanfeng Sun; Junbin Gao; Yongli Hu; Baocai Yin
Page(s): 588 - 600

22. Dendritic Neuron Model With Effective Learning Algorithms for Classification, Approximation, and Prediction
Author(s): Shangce Gao; Mengchu Zhou; Yirui Wang; Jiujun Cheng; Hanaki Yachi; Jiahai Wang
Page(s): 601 - 614

23. Multiclass Nonnegative Matrix Factorization for Comprehensive Feature Pattern Discovery
Author(s): Yifeng Li; Youlian Pan; Ziying Liu
Page(s): 615 - 629

24. Self-Paced Learning-Based Probability Subspace Projection for Hyperspectral Image Classification
Author(s): Shuyuan Yang; Zhixi Feng; Min Wang; Kai Zhang
Page(s): 630 - 635

25. Hierarchical Stability Conditions for a Class of Generalized Neural Networks With Multiple Discrete and Distributed Delays
Author(s): Lei Song; Sing Kiong Nguang; Dan Huang
Page(s): 636 - 642

Thursday, 21 February 2019

Full UK PhD Scholarships

Full UK PhD scholarships in evolutionary computation/ computational intelligence/data analytics/ operations research/optimisation/simulation

Thanks to an arisen opportunity, we at the Operational Research (OR) group, Liverpool John Moores University (United Kingdom) may be able to offer a small number of PhD scholarships (full or tuition-fees-only depending on the quality of the candidate).

There are two types of scholarships:

The ones for UK/EU/settled students:
  • Deadline 3rd March. Results to be known by end of March.
  • provide full tuition fees for three years and,
  • living expenses + running cost cover of about £16,500 each year (to be determined) for 3 years
  • students have to enrol in Sept-Oct 2019
  • Brexit will not have any impact on these scholarships

The ones for international students:
  • Provide about £20,000 each year (to be determined). Students can use this amount to pay toward their tuition fees and living expenses.
  • If the successful candidate joins one of the projects currently being run by the OR group, he/she may get additional scholarships depending on research performance and level of contribution.
Regarding research topic, any area in evolutionary computation/ computational intelligence/data analytics/ operations research would be acceptable. However, I would prefer a topic that relates to one of our existing projects, which are in the following areas:

  • OR techniques to study/mitigate the impact of climate change on transportation. For example, we have a project (with Merseyrail and Network Rail) on using data analytics and optimisation to anticipate and mitigate the impact of leaves falling on train tracks.
  • Evolutionary computation or meta-heuristics
  • OR/data analytics applications in rail, in partnership with Merseyrail, Network Rail, and Rail Delivery Group
  • OR applications in maritime, in partnership with UK, EU and overseas ports
  • OR applications in sustainable transportation, e.g. bicycle, e-bikes, walking, buses, emission/congestion reduction etc., in partnership with local authorities and transport authorities (e.g. the ones in Liverpool and Manchester)
  • OR applications in logistics (e.g. bin packing, vehicle routing etc.) in partnership with logistics companies, especially those in airports, ports, and manufacturing plants (especially those in Liverpool).
  • OR applications in manufacturing, in partnership with car manufacturers e.g. Vauxhall and Jaguar Land Rover.

Interested candidates please contact Dr. Trung Thanh Nguyen with your full CV and transcripts. It is important that interested candidates contact me ASAP to ensure that we can prepare your applications in the best way to maximise your chance before the deadline of 3rd March.

Sunday, 17 February 2019

Call-for-Papers: The 3rd International Symposium on Autonomous Systems

The 3rd International Symposium on Autonomous Systems
(ISAS 2019) May 29-31, 2019, Shanghai, China (

On behalf of the ISAS 2019 Organizing Committee, this is to invite you to submit your contributions to The 3rd International Symposium on Autonomous Systems (ISAS 2019), May 29-31, 2019, Shanghai, China ( The 3rd International Symposium on Autonomous Systems, ISAS 2019, will be held in Shanghai, China, during May 29-31, 2019. The conference is organized by Chongqing University, Shanghai Jiao Tong University, China, Star Institute for Intelligent Systems, China, University of Texas at Arlington, USA, and technically co-sponsored by IEEE Computational Intelligence Society, Technical Committee on Reliable Control Systems, Chinese Association of Automation, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, China, and Key Laboratory of System Control and Information Processing, Ministry of Education of China. ISAS focuses on both theory and applications mainly covering the topics of artificial intelligence, control, automation, robotics and autonomous systems. In addition to the technical sessions, there will be invited sessions, panel sessions and keynote addresses. The topics of interest include, but are not limited to:

  • Artificial intelligence (AI): Artificial intelligence and philosophy, Automated reasoning and inference, Case-based reasoning, Cognitive aspects of AI, Commonsense reasoning, Constraint processing, Heuristic search, High-level computer vision, Intelligent interfaces, Intelligent robotics, Knowledge representation, Machine learning, Multi-agent systems, Natural language processing, Planning and theories of action, Reasoning under uncertainty or imprecision
  • Autonomous Systems: Unmanned system command and control, Cooperative control of unmanned systems, Unmanned system modeling and simulation, Unmanned system dynamics, New concept unmanned systems, Robotic systems, Unmanned aerial vehicles
  • Networked Control Systems: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems
  • Intelligent Control: Adaptive control, Co-operative control, Intelligent systems, Discrete event systems, Multi-agent systems, Neural networks, Fuzzy systems, Control of biological systems
  • Automation: Man-machine interactions, Process automation, Intelligent automation, Factory modeling and simulation, Home, laboratory and service automation, Network-based systems, Planning, scheduling and coordination, Nano-scale automation and assembly, Instrumentation systems, Biomedical instrumentation and applications, Building energy efficiency
  • Robotics: Modeling and identification, Robot control, Mobile robotics, Mobile sensor networks, Perception systems, Micro robots and micro-manipulation, Visual servoing, Search, rescue and field robotics, Robot sensing and data fusion, Localization, navigation and mapping, Dexterous manipulation, Medical robots and bio-robotics, Human centered systems, Space and underwater robots, Tele-robotics, Mechanism design and applications.
  • Emerging Technologies: Internet of things, Cyber-physical systems, Smart buildings, Smart grid, Energy management systems, Big data, Electric vehicles and intelligent transportation.
Keynote Speeches:
  • Professor Jie Chen, Tongji University
  • Professor Jie Huang, The Chinese University of Hong Kong
  • Professor Marios Polycarpou, University of Cyprus
  • Professor Jose Principe, University of Florida
Important Dates (Please check the latest information at
  • February 28, 2019: Extended Deadline for Invited Session Proposals
  • February 28, 2019: Extended Deadline for Full Paper Submission
  • March 28, 2019: Notification of Acceptance/Rejection
  • April 15, 2019: Deadline for Camera Ready Manuscript Submission
  • April 15, 2019: Deadline for Advance Registration

Welcome and look forward to receiving your contributions and attendance to the ISAS 2019!

Frank L. Lewis, University of Texas at Arlington, USA
Hailong Pei, South China University of Technology, China
Yongduan Song, Chongqing University, China
Ning Li, Shanghai Jiao Tong University, China
Kimon P. Valavanis, Denver University, USA
Youmin Zhang, Concordia University, Canada
Tianyou Chai, Northeastern University, China

Frank Lewis, U of Texas at Arlington,

Yongduan Song, Chongqing University,
Xinping Guan, Shanghai Jiao Tong University,


ChangyunWen, Nanyang technological University,
Cailian Chen, Shanghai Jiao Tong University,

Wednesday, 13 February 2019

Call for Nominations / Applications for the position of Editor-in-Chief of the IEEE Computational Intelligence Magazine

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE CIS). Additionally, CIM serves as a media of communications between the governing body and its membership of IEEE CIS. Authors are encouraged to submit papers on applications oriented developments, successful industrial implementations, design tools, technology reviews, computational intelligence education, and applied research. Details about the current state of this publication can be found at:

The inaugural issue of CIM was published in February 2006 as the official magazine of IEEE Computational Intelligence Society (CIS).  Gary G. Yen worked hard for CIM as the founding Editor-in-Chief from 2006 to 2009 until Kay Chen Tan assumed the reins in 2010. Hisao Ishibuchi took over these duties in 2014, and his term is completing in 2019. Through their dedicated effort, and with generous support from the members of CIS, the magazine has become one of the most successful and influential periodical publications in the field of computational intelligence.  Its impact, along with its Impact Factor, has grown steadily over the years.  Thanks to the hard work of the EiCs, this technical and societal material is packaged in a classy format, a proud addition to the CIS publication portfolio.

Because Hisao’s term is ending, a new Editor-in-Chief must be appointed to assume leadership in 2020. The IEEE CIS Executive Committee has formed an Adhoc Search Committee to seek suitable candidates to serve as the next EiC of CIM. The Search Committee solicits nominations/applications for this position. Nominees/applicants should be dedicated volunteers with outstanding research profiles and extensive editorial experience. The nomination/application package should include complete CV along with a separate description (max 300 words/topic) on each of the following items:

  • Vision Statement
  • Understanding of the differences between EiC duties of a magazine and journal
  • Challenges, if any, faced by the publication, and a plan to deal with them
  • Editorial Experience
  • Summary of publishing experience in IEEE magazines/journals
  • IEEE Volunteer Experience
  • Institutional Support
  • Current service and administrative commitments
  • Networking with the Community
  • Statement of why the candidate considers himself/herself fit for this position? 

Address any questions, and send the nomination/application package as a single PDF file through email to by April 26, 2019.  

Jim Keller, Chair of the Search Committee
Hisao Ishibuchi
Chin-Teng Lin
Pablo Estevez
Kay Chen Tan

Thursday, 7 February 2019

CFP: IEEE Conference on Games (COG) 2019

20-23 August 2019
Queen Mary University of London, UK

The IEEE Conference on Games (IEEE CoG) is a natural evolution of the IEEE Computational Intelligence and Games (IEEE CIG) to embrace a larger scope, in line with the IEEE Transactions on Games. The conference will bring together leading researchers and practitioners from academia and industry in the field of Games, to discuss recent advances and explore future directions. Games offer an excellent domain for the study and application of many research areas including artificial intelligence, computational creativity, game design, technology, education social sciences. The annual IEEE Conference on Games seeks to share insights and cutting-edge research related to game technologies and design, covering scientific, technical, and engineering aspects of games. The conference will also include a varied set of competitions for AI agents where the AI either aims to play games to a high standard, or design new games or game levels.


IEEE CoG 2019 will include presentations of peerreviewed papers, invited talks by high-profile industry and academic leaders, panels, posters and demos. We welcome papers related to all aspects of games, including, but not limited to, the following broad subject areas:

Computational and Artificial Intelligence in Games: advances in and applications of machine learning, search, reasoning, optimization and other CI/AI methods related to video games, board games, computer games, serious games, mathematical games and other types of games. This includes, but is not limited to, methods for game playing, content generation, player modeling, and game adaptation, as well as game-based testing of AI methods.

  • Game Technology: papers on engines, frameworks, graphics, sound, networking and animation.
  • Game Interaction and Player Experience: advances in game interfaces and modeling of player experience and metrics.
  • Game Design: methods, techniques and studies on video and board game design.
  • Games in Education: usage of games for education, learning and development. This includes game competitions used for teaching and research in education institutions.

None of the deadlines will be extended!

Full technical papers: 24th March 2019
Short, competition, vision and demo papers: 14th May 2019
Games Industry track: 11th June 2019


General Chairs:
Diego Perez-Liebana {} &
Sanaz Mostaghim {}

Program Chairs: Amy K. Hoover &
Simon M. Lucas & Georgios Yannakakis

Local Chair: Laurissa Tokarchuck

Keynote Chair: Jichen Zhu

Tutorial Chair: Gillian Smith

Competition Chairs: Julian Togelius &
Mike Preuss

Industry Chairs: Sam Devlin & Xenia Neufeld &
Duygu Cakmak & Anders Drachen

Special Session Chair: Dan Ashlock

Finance Chair: Mark Winands

Proceedings Chair: Vanessa Volz

Demonstrations Chair: Antonios Liapis

Publicity and Media Chairs: Raluca D. Gaina &
Jialin Liu

Webmaster: Cristina Guerrero-Romero

Monday, 4 February 2019

CFP: CEC 2019 workshop "Understanding of Evolutionary Optimization Behavior"


We are organising the workshop “Understanding of Evolutionary Optimization Behavior (UEOB 2019)” at the IEEE Congress on Evolutionary Computation 2019 ( in Wellington, New Zealand.

Please consider to contribute to and/or forward to the appropriate groups the following opportunity to present original research articles in CEC 2019.


The focus of the UEOB 2019 is to highlight theoretical and empirical research that investigates approaches needed to analyze stochastic optimization algorithms and performance assessment with regard to different criteria. The main goal is to bring the problem and importance of understanding optimization algorithms closer to researchers and to show them how and why this is important for future development in the optimization community. This will help researchers/users to transfer the gained knowledge from theory into the real world, or to find the algorithm that is best suited to the characteristics of a given real-world problem.

More detailed information can be found at

  • Data-driven approaches (machine learning/information theory/statistics) for assessing algorithm performance
  • Vector embeddings of problem search space
  • Meta-learning
  • New advances in analysis and comparison of algorithms
  • Operators influence on algorithm behavior
  • Parameters influence on algorithm behavior
  • Theoretical algorithm analysis


All submissions should be formatted according to the CEC 2019 submission guidelines provided at
All submissions will be handled through EasyChair ( and reviewed by the program committee.

In order to participate to this workshop, a full or a student registration at CEC 2019 is required.

Selected papers will be invited to be extended for a special issue in Natural Computing (

  • Paper submission: 15 March, 2019
  • Notification to authors: 31 March, 2019
  • Early registration: 31 March, 2019
  • Final submission: 15 April, 2019
  • Conference: 10-13 June, 2019


Tome Eftimov
Department of Biomedical Data Sciences, Stanford Medicine
Stanford University

Peter Korošec
Computer Systems Department
Jožef Stefan Institute

Christian Blum
Artificial Intelligence Research Institute (IIIA)
Spanish National Research Council (CSIC)

Saturday, 2 February 2019


16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology

July 9-11, 2019

Certosa di Pontignano, Tuscany, Italy

General chair: Giuseppe Nicosia
Program chair: Barbara Di Camillo
Finance chair: Renato Umeton
Technical co-chairs: Richard Allmendinger, Simone Furini, Emanuele Domenico Giordano
Publicity / proc. co-chairs: Giacomo Baruzzo, Alessandro Zandona

Keynote Speakers:
Pierre Baldi, USA
Riccardo Bellazzi, Italy
Thomas Keane, UK

Saturday, 5 January 2019

CFP: International Conference on Advanced Computational Intelligence (ICACI 2019) (15 Jan)

The Eleventh International Conference on Advanced Computational Intelligence (ICACI2019) will be held in Guilin, China during June 7-9, 2019. ICACI2019 aims to provide a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research and applications in computational intelligence. The conference will feature plenary speeches given by world renowned scholars, regular sessions with broad coverage, and special sessions focusing on popular topics. In addition, best paper awards will be given during the conference. The proceedings of ICACI2019 will be submitted for inclusion into the IEEE Xplore Database which is indexed by EI Compendex and Scopus. Moreover, selected papers with extended version will be recommended to publish in special issues of related journals. The conference will favor papers representing advanced theories and innovative applications in computational intelligence.

Prospective authors are invited to contribute high-quality papers to ICACI2019. In addition, proposals for special sessions within the technical scopes of the conference are solicited. Special sessions, to be organized by internationally recognized experts, aim to bring together researchers in special focused topics. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information and brief biographical information on the organizers.

Topics Areas

Topics areas include, but not limited to, computational neuroscience, connectionist theory and cognitive science, mathematical modeling of neural systems, neurodynamic analysis, neurodynamic optimization, adaptive dynamic programming, embedded neural systems, probabilistic and information-theoretic methods, principal and independent component analysis, hybrid intelligent systems, supervised, unsupervised and reinforcement learning, deep learning, brain imaging and neural information processing, neuroinformatics and bioinformatics, support vector machines and kernel methods, autonomous mental development, data mining, pattern recognition, time series analysis, image and signal processing, robotic and control applications, telecommunications, transportation systems, intrusion detection and fault diagnosis, hardware implementation, real-world applications, big data processing, fuzzy systems, fuzzy logic, fuzzy set theory, fuzzy decision making, fuzzy information processing, fuzzy logic control, evolutionary computation, ant colony optimization, genetic algorithms, parallel and distributed algorithms, particle swarm optimization, differential evolution, evolving neural networks, evolutionary fuzzy systems, evolving neuro-fuzzy systems, evolutionary games and multi-agent systems, intelligent systems applications.

Important Dates

Special session proposals deadline: Dec. 1, 2018
Paper submission deadline(extented): Jan. 1, 2019 Jan. 15, 2019
Notification of acceptance: Mar. 1, 2019
Camera-ready copy and author registration: Apr. 1, 2019

Instructions for authors:

1. Paper Format: Please use the A4 format, Times New Roman of font size 10, single spaced, and two columns. Do not number your manuscript pages and do not use the US letter format. Please use the IEEE template (Microsoft Word or Latex) to prepare your manuscript. The templates are available from:

2. We can only accept PDF files. All submitted papers should be limited to a maximum length of 6 pages, including figures, tables, and references. Up to two additional pages will be permitted for a charge of USD 160 per additional page.

3. The Submission will be done via EasyChair system:


General Chairs

Tianlong Gu, Guilin University of Electronic Technology, Guilin, China
Xiaonan Luo, Guilin University of Electronic Technology, Guilin, China
Jun Zhang, South China University of Technology, Guangzhou, China

Advisory Chairs

C. L. Philip Chen, University of Macau, Macao
Xin Yao, University of Birmingham, Birmingham, UK, and Southern University of Science and Technology, Shenzhen, China
Gary G. Yen, Oklahoma State University, Stillwater, OK, USA

Steering Chairs

Derong Liu, University of Illinois – Chicago, Chicago, USA
Jun Wang, City University of Hong Kong, Hong Kong

Organizing Chair

Liang Chang, Guilin University of Electronic Technology, Guilin, China

Program Chairs

Chia-Feng Juang, National Chung-Hsing University, Taichung, Taiwan
Zhihui Zhan, South China University of Technology, Guangzhou, China
Nian Zhang, University of District of Columbia, Washington, USA

Special Sessions Chairs

Tingwen Huang, Texas A&M University –Qatar, Qatar
Zhiwen Yu, South China University of Technology, Guangzhou, China
Dongbin Zhao, University of Chinese Academy of Sciences, Beijing, China

Publicity Chairs

Jinde Cao, Southeast University, Nanjing, China
Min Han, Dalian University of Technology, Dalian, China
Yuanqing Li, South China University of Technology, Guangzhou, China
Zhang Yi, Sichuan University, Chengdu, China
Zhigang Zeng, Huazhong University of Science and Technology, Wuhan, China

Publications Chairs

Yuejiao Gong, South China University of Technology, Guangzhou, China
Qiuyuan Luo, South China University of Technology, Guangzhou, China
Zhenbing Liu, Guilin University of Electronic Technology, Guilin, China
Huadeng Wang, Guilin University of Electronic Technology, Guilin, China

Registration Chairs

Ziming Wang and Jiayu Huang, Guilin University of Electronic Technology, Guilin, China

Local Arrangements Chairs

Rushi Lan and Li Li, Guilin University of Electronic Technology, Guilin, China

CFP: IEEE CEC 2019 Special Session on When Evolutionary Computation Meets Data Mining

Many of the tasks carried out in data mining and machine learning, such as feature subset selection, associate rule mining, and model building, can be transformed as optimization problems. Thus it is very natural that Evolutionary Computation (EC), has been widely applied to these tasks in the fields of data mining (DM) and machine learning (ML), as an optimization technique.

On the other hand, EC is a class of population-based iterative algorithms, which generate abundant data about the search space, problem feature and population information during the optimization process. Therefore, the data mining and machine learning techniques can also be used to analyze these data for improving the performance of EC. A lot of successful applications have been reported, including the creation of new optimization paradigm such as Estimation of Distribution Algorithm, the adaptation of parameters or operators in an algorithm, mining the external archive for promising search regions, and so on.

However, there remain many open issues and opportunities that are continually emerging as intriguing challenges for bridging the gaps between EC and DM. The aim of this special session is to serve as a forum for scientists in this field to exchange the latest advantages in theories, technologies, and practice.

We invite researchers to submit their original and unpublished work related to, but not limited to, the following topics:

  • EC enhanced by Data Mining and Machine Learning Concepts and/or Framework
  • Data Mining and Machine Learning Based on EC techniques
  • Machine Learning Enhanced and/or Model-based Multi- and/or Many-objective Optimization
  • Data Mining and Machine Learning Enhanced Constrained Optimization:
  • Data Mining and Machine Learning Enhanced Memetic Computation or Local Search
  • Data Mining and Machine Learning Enhanced EC for Combinatorial Optimization
  • Data Mining and Machine Learning Enhanced EC for Large-scale Optimization
  • Data Mining and Machine Learning Enhanced EC for Dynamic Optimization
  • Association Rule Mining Based on Multi-Objective Optimization
  • Knowledge Discovery in Data Mining via Evolutionary Algorithm
  • Genetic Programming in Data Mining
  • Multi-Agent Data Mining using Evolutionary Computation
  • Medical Data Mining with Evolutionary Computation
  • Evolutionary Computation in Intelligent Network Management
  • Evolutionary Clustering in Noisy Data Sets
  • Big Data Projects with Evolutionary Computation
  • Deep Learning with Evolutionary Computation
  • Real World Applications

Paper Submission:

All papers should be submitted electronically through IEEE CEC 2017 website at To submit your papers to the special session, please select the Special Session in the Main Research topic. For more submission information please visit: All accepted papers will be published in the IEEE CEC 2017 electronic proceedings.


Zhun Fan
Shantou University, China

Xinye Cai
Nanjing University of Aeronautics and Astronautics, China

CFP: IEEE CEC 2019 Special Session on Evolutionary Computation for Music, Art, and Creativity

Creativity and Intelligence are both terms that have been deeply studied for centuries but still generate debates. Scholars frequently relate both terms, establishing connections that allows to understand the relationship between general intelligence and creativity. Both are considered required for addressing challenging problems, and also for creating art or appealing designs. Music, Literature, Architecture, Painting, Crafts, Industrial Design,... all could benefit from a better understanding and conceptualization of the processes behind Creativity and Intelligence. Although computers have exceeded the capabilities of humans in a number of limited domains, human creativity generally remains unchallenged, and only recently some techniques, such as Computational Intelligence, have begun to address problems related to creativity. Computational Intelligence (CI) is a term that embodies a number of nature-inspired techniques. CI includes Evolutionary Computation, Neural Networks, Fuzzy logic Systems and other techniques derived from them, such as Swarm Optimization, Artificial Immune Systems, Ant Colony Optimization to name but a few. CI is routinely applied nowadays to solving complex real life problems. Despite the great variety of methods and applications, only very recently, researchers have considered the capabilities of CI when applied to creative processes. Nevertheless, the finding of a general model for creativity and its relationship with Intelligence is far to be found.


This task force aims at promoting the study of Creativity and its connection to Intelligence from the point of view of Computational Intelligence. The task force will promote the study of computational creative discovery by means of CI, with the aim of both enhancing human creativity and also generation of autonomous creative behaviors. Artist creation will be an area of research: we will pay attention to visual art and music composition. We will pursue the application of CI to any branch of Art and Design, included but not limited to Architecture, Painting, Music, Literature, to name but a few.

The task force will also be interested in the study of the underlying mental processes leading to creativity, and their translation to hardware and software implementation.

The task force will be appealing for researchers from a variety of disciplines and backgrounds, with coverage across the arts and sciences, with interest in the application of an interdisciplinary approach.


The scope of this task force include the following topics:

  • Contribute to fundamental understanding of artistic creativity.
  • Contribute to Computational Intelligence approaches to creativity in humans and machines.
  • Develop new CI based methodologies for generation of music, visual art, literature, architecture, and industrial design.
  • Develop new methodologies based on evolutionary ecosystems dynamics for creative discovery.
  • Develop new methodologies allowing the interaction between human and computer based creativity.
  • Studying hardware platforms and software implementation leading to better creative systems.

Chuan-Kang Ting, National Chung Cheng University, Taiwan

Francisco Fernández de Vega, University of Extremadura, Spain

Further information:

CFP: IEEE CEC 2019 Special Session on Data-Driven Evolutionary Optimization of Computationally Expensive Problems

Meta-heuristic algorithms, including evolutionary algorithms and swarm optimization, face challenges when solving time-consuming problems, as typically these approaches require thousands of function evaluations to arrive at solutions that are of reasonable quality. Surrogate models, which are computationally cheap, have in recent years gained in popularity in assisting meta-heuristic optimization, by replacing the compute-expense/time-expensive problem during phases of the heuristic search. However, due to the curse of dimensionality, it is very difficult, if not impossible to train accurate surrogate models. Thus, appropriate model management techniques, memetic strategies and other schemes are often indispensable. In addition, modern data analytics involving advance sampling techniques and learning techniques such as semi-supervised learning, transfer learning and active learning are highly beneficial for speeding up evolutionary search while bringing new insights into the problems of interest. This special session aims at bringing together researchers from both academia and industry to explore future directions in this field. 

Scope and Topics

The topics of this special issue include but are not limited to the following topics:

  • Surrogate-assisted evolutionary optimization for computationally expensive problems
  • Adaptive sampling using machine learning and statistical techniques
  • Surrogate model management in evolutionary optimization
  • Data-driven optimization using big data and data analytics
  • Knowledge acquisition from data and reuse for evolutionary optimization
  • Computationally efficient evolutionary algorithms for large scale and/or many-objective optimization problems
  • Real world applications including multi-disciplinary optimization.

Important Dates

Submission deadline:7 January 2019
Notification: 7 March 2019
Final paper submission: 31 March 2019
Early Registration: 31 March 2019


The papers must be submitted online through the manuscript submission system ( 


Prof. Chaoli Sun, Department of Computer Science and Technology, Taiywan University of Science and Technology, China. 

Prof. Jonathan Fieldsend, Department of Computer Science, University of Exeter, United Kingdom. 

Prof. Yew-Soon Ong, School of Computer Engenieering, Nanyang Technological University, Singapore. 

CFP: IEEE CEC 2019 Special Session on Memetic Computing

Memetic Computing (MC) represents a broad generic framework using the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. In the literature, MC has been successfully manifested as memetic algorithm, where meme has been typically perceived as individual learning procedures, adaptive improvement procedures or local search operators that enhance the capability of population based search algorithms. More recently, novel manifestations of meme in the forms such as knowledge building-block, decision tree, artificial neural works, fuzzy system, graphs, etc., have also been proposed for efficient problem-solving. These meme-inspired algorithms, frameworks and paradigms have demonstrated with considerable success in various real-world applications.

The aim of this special session on memetic computing is to provide a forum for researchers in this field to exchange the latest advances in theories, technologies, and practice of memetic computing.

Scope and Topics

The scope of this special session covers, but is not limited to:

  • Single/Multi-Objective memetic algorithms for continuous or combinatorial optimization
  • Theoretical studies that enhance our understandings on the behaviors of memetic computing
  • Adaptive systems and meme coordination
  • Novel manifestations of memes for problem-solving
  • Cognitive, Brain, individual learning, and social learning inspired memetic computation
  • Self-design algorithms in memetic computing
  • Memetic frameworks using surrogate or approximation methods
  • Memetic automaton, cognitive and brain inspired agent based memetic computing
  • Data mining and knowledge learning in memetic computation paradigm
  • Memetic computing for expensive and complex real-world problems
  • Evolutionary multi-tasking

Paper Submission

Papers for IEEE CEC 2019 should be submitted electronically through the Congress website at, and will be refereed by experts in the fields and ranked based on the criteria of originality, significance, quality and clarity. To submit your papers to the special session, please select the Special Session name in the Main Research topic.

For more submission information please visit:
All accepted papers will be published in the IEEE CEC 2019 electronic proceedings, included in the IEEE Xplore digital library, and indexed by  EI Compendex. High quality papers will be invited to extend and submit to the Memetic Computing Journal.

Important Dates

Submission Deadline: January 7, 2019
Notification of Acceptance: March 7, 2019

CFP: IEEE CEC 2019 Special Session on Speciation

Although Evolutionary Algorithms are very good at mimicking adaptation within a species to optimize solutions for difficult problems, creating algorithms that can mimic the development of two or more species from a common ancestor has been a challenge. There are versions of Evolutionary Algorithms that have some characteristics of speciation, but none that match natural processes. Such algorithms would be a good step in the development of a general purpose Evolutionary Algorithm and would help in understanding the principles of evolution. In regards to this research, we consider a population to be distinct (and a separate species) if it is made up of individuals that are unable to produce viable offspring with individuals from the other population or if offspring are produced, they are sterile. The short term goal, which is reasonable for this special session, is to have individuals of differing species choose not to mate and if they do produce offspring, the offspring do not continue to reproduce. In this way, the gene pools for each of the species will be isolated.

The purpose of this special session is to bring together people working on Evolutionary Algorithms that tend toward or have the potential for speciation. Some possible topics of interest include:

  • Evolutionary algorithms mimicking allopatric or sympatric speciation
  • Environments for research in natural speciation
  • Biologically-inspired models of interactive agents
  • Spatially-structured populations
  • Niching
  • Island models
  • Use of topology in populations
  • Formation of sub-populations
  • Selection criteria in evolutionary algorithms
  • Co-evolution
  • Multi-agent systems
  • Multimodal function optimization

Paper Submission

Papers should be submitted through the IEEE CEC 2019 paper submission website. Please specify that your paper is submitted to the Special Session on Speciation. All papers accepted and presented at CEC2019 will be included in the conference proceedings.

The submission deadline, date of notification, and the final paper submission dealine are the same as for regular conference papers -- these dates can be found at


Gary Parker - Department of Computer Science, Connecticut College, New London, Connecticut, USA

Peter Whigham - Department of Information Science, University of Otago, Dunedin, Otago, New Zealand.

Thursday, 3 January 2019


IEEE WCCI 2020 IEEE World Congress on Computational Intelligence 19th - 24th July 2020 Glasgow                                Glasgow, Scotland, UK []

The IEEE World Congress on Computational Intelligence (IEEE WCCI)isthe world's largest technical eventinthe field of computational intelligence. The IEEE WCCI 2020 will host three conferences: The 2020 InternationalJointConference on Neural Networks (IJCNN2020),the 2020IEEEInternationalCon­ferenceon FuzzySystems (FUZZ-IEEE 2020), and the 2020 IEEECongresson Evolutionary Computation (IEEECEC2020) under oneroof. Itencourages cross-fertilisationof ideasamong the threebigareas and provides a forum for intellectuals from all over the world to discuss and present their research findings on computational intelligence.

IEEE WCCI 2020 will be held in Glasgow - one of Europe's most dynamic cultural capitals and the "world's friendliest city" - located in Scotland, "the most beautiful country in the world" [Rough Guides 2015, 2017]. Steeped in cul­ture, rich in history and alive with an excitement visitors will sense as they walk through its elegant Victorian streets, squares, parks and gardens. The Conference is being hosted at the prestigious Scottish Event Campus (SEC), which was a key venue for the Glasgow Commonwealth Games 2014 [•uk/ ].
IJCNN is the flagship conference of the International Neural Network Society and the IEEE Computational Intelli­gence Society. It covers a wide range of topics in the field of neural networks, from biological neural network mod­elling to artificial neural computation.
FUZZ-IEEE is the foremost conference in the field of fuzzy systems. It covers all topics in fuzzy systems, from theory to applications.
IEEE CEC is the leading event in the field of evolutionary computation, and covers all topics in evolutionary compu­tation from theory to applications.
Important Dates
Nov 2019 Special Session & Workshop Proposals Deadline 
15 Dec 2019 Competition and Tutorial Proposals Deadline
15 Jan 2019 Paper Submission Deadline
15 Mar 2020 Paper Acceptance Notification Date
15 April 2020 Final Paper Submission and Early Registration Deadline 
19-24 July 2020 IEEE WCCI 2020, Glasgow, Scotland, UK

Register your interest online (http://wcci2020.orgfor regular updates

Call for Papers
Electronic submission of papers for IEEE WCCI 2020 will be required through the Congress website at www.wcci2020.orgAll papers will be refereed by experts in the fields and ranked based on the criteria of original­ity, significance, quality and clarity. See Important Dates above.

Call for Tutorials
IEEE WCCI 2020 will solicit proposals for tutorials offering a unique opportunity to disseminate in-depth informa­tion on specific topics in computational intelligence. Tutorials will be organized by scientists or professionals who have significant expertise in the selected topic and whose recent work has had a significant impact in their field. For enquiries, please contact the Tutorials Co-Chair most appropriate to your topic.

Call for Special Sessions
IEEE WCCI 2020 will solicit proposals for Special Sessions within the technical scope of the three conferences. Spe­cial Sessions are expected to be organised by internationally recognised experts, with aims to bring together re­searchers in special focused topics. Cross-fertilisation of the three technical disciplines and newly emerging re­search areas are strongly encouraged. Inquiries should be addressed to the Special Session co-Chair most appropri­ate to your topic.

Call for Workshops
IEEE WCCI 2020 will solicit proposals for half or full-day workshops to provide participants with the opportunity to present and discuss novel research ideas on active and emerging CI topics, challenging problems and/or industrial applications. Workshop organizers are encouraged to make their workshops highly interactive, and include discus­sions, Q&A and panel sessions to facilitate a lively exchange of ideas among the attendees. Inquiries regarding should be addressed to the Workshops Chairs.

Call for Competitions
IEEE WCCI 2020 will host competitions to stimulate research in computational intelligence. A competition proposal should include descriptions of the problem(s) addressed, evaluation procedures, and a biography of the organisers. Inquiries regarding competitions should be addressed to the Competitions Chairs.

General Co-Chairs
Amir Hussain, UK
Manes M. Polycarpo, Cyprus Xin Yao, China
IJCNN Conference Chair Asim Roy, USA
IJCNN Technical Chairs
Peter Erdi, USA
Daniel S. Levine, USA Danilo Mandic, UK Chrisina Jayne, UK
FUZZ-IEEEConference Chair Nikhil R Pal, India
FUZZ-IEEETechnicalChairs Oscar Cordon, Spain
Hani Hagras, UK
Hak-Keung Lam, UK Chin-Teng Lin, Australia
IEEECECConference Chair Yaochu Jin, UK
IEEE CEC Technical Chairs Hisao Ishibuchi, Japan
ling Liu, China
Dipti Srinivasan, Singapore Andy Tyrrell, UK

For all WCCI Chairs please visit conference website