IEEE Transaction on Fuzzy System, Volume 26, Issue 3, June 2018

1. Lagrange Stability for T–S Fuzzy Memristive Neural Networks with Time-Varying Delays on Time Scales
Author(s): Q. Xiao and Z. Zeng
Page(s): 1091-1103
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7927477&isnumber=8370013

2. A T–S Fuzzy Model Identification Approach Based on a Modified Inter Type-2 FRCM Algorithm
Author(s): W. Zou, C. Li and N. Zhang
Page(s): 1104-1113
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7930413&isnumber=8370013

3. Sensor Fault Estimation of Switched Fuzzy Systems With Unknown Input
Author(s): H. Zhang, J. Han, Y. Wang and X. Liu
Page(s): 1114-1124
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7929306&isnumber=8370013

4. Fuzzy Remote Tracking Control for Randomly Varying Local Nonlinear Models Under Fading and Missing Measurements
Author(s): J. Song, Y. Niu, J. Lam and H. K. Lam
Page(s): 1125-1137
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7931574&isnumber=8370013

5. Distributed Adaptive Fuzzy Control for Output Consensus of Heterogeneous Stochastic Nonlinear Multiagent Systems
Author(s): S. Li, M. J. Er and J. Zhang
Page(s): 1138-1152
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7937827&isnumber=8370013

6. Adaptive Fuzzy Control With Prescribed Performance for Block-Triangular-Structured Nonlinear Systems
Author(s): Y. Li and S. Tong
Page(s): 1153-1163
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7937916&isnumber=8370013

7. Dissipativity-Based Fuzzy Integral Sliding Mode Control of Continuous-Time T-S Fuzzy Systems
Author(s): Y. Wang, H. Shen, H. R. Karimi and D. Duan
Page(s): 1164-1176
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7937910&isnumber=8370013

8. A Layered-Coevolution-Based Attribute-Boosted Reduction Using Adaptive Quantum-Behavior PSO and Its Consistent Segmentation for Neonates Brain Tissue
Author(s): W. Ding, C. T. Lin, M. Prasad, Z. Cao and J. Wang
Page(s): 1177-1191
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7953563&isnumber=8370013

9. Fuzzy Model Predictive Control of Discrete-Time Systems with Time-Varying Delay and Disturbances
Author(s): L. Teng, Y. Wang, W. Cai and H. Li
Page(s): 1192-1206
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7953664&isnumber=8370013

10. Finite-Time Adaptive Fuzzy Tracking Control Design for Nonlinear Systems
Author(s): F. Wang, B. Chen, X. Liu and C. Lin
Page(s): 1207-1216
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7953644&isnumber=8370013

11. Combination of Classifiers With Optimal Weight Based on Evidential Reasoning
Author(s): Z. G. Liu, Q. Pan, J. Dezert and A. Martin
Page(s): 1217-1230
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7956193&isnumber=8370013

12. Evaluating and Comparing Soft Partitions: An Approach Based on Dempster–Shafer Theory
Author(s): T. Denœux, S. Li and S. Sriboonchitta
Page(s): 1231-1244
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7954636&isnumber=8370013

13. Adaptive Tracking Control for a Class of Switched Nonlinear Systems Under Asynchronous Switching
Author(s): D. Zhai, A. Y. Lu, J. Dong and Q. Zhang
Page(s): 1245-1256
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7959189&isnumber=8370013

14. Incremental Perspective for Feature Selection Based on Fuzzy Rough Sets
Author(s): Y. Yang, D. Chen, H. Wang and X. Wang
Page(s): 1257-1273
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7959194&isnumber=8370013

15. Galois Connections Between a Fuzzy Preordered Structure and a General Fuzzy Structure
Author(s): I. P. Cabrera, P. Cordero, F. García-Pardo, M. Ojeda-Aciego and B. De Baets
Page(s): 1274-1287
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7954674&isnumber=8370013

16. IC-FNN: A Novel Fuzzy Neural Network With Interpretable, Intuitive, and Correlated-Contours Fuzzy Rules for Function Approximation
Author(s): M. M. Ebadzadeh and A. Salimi-Badr
Page(s): 1288-1302
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7954716&isnumber=8370013

17. On Using the Shapley Value to Approximate the Choquet Integral in Cases of Uncertain Arguments
Author(s): R. R. Yager
Page(s): 1303-1310
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7955006&isnumber=8370013

18. Adaptive Fuzzy Sliding Mode Control for Network-Based Nonlinear Systems With Actuator Failures
Author(s): L. Chen, M. Liu, X. Huang, S. Fu and J. Qiu
Page(s): 1311-1323
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7955022&isnumber=8370013

19. Correntropy-Based Evolving Fuzzy Neural System
Author(s): R. J. Bao, H. J. Rong, P. P. Angelov, B. Chen and P. K. Wong
Page(s): 1324-1338
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7956185&isnumber=8370013

20. Multiobjective Reliability Redundancy Allocation Problem With Interval Type-2 Fuzzy Uncertainty
Author(s): P. K. Muhuri, Z. Ashraf and Q. M. D. Lohani
Page(s): 1339-1355
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7964733&isnumber=8370013

21. Distributed Adaptive Fuzzy Control For Nonlinear Multiagent Systems Under Directed Graphs
Author(s): C. Deng and G. H. Yang
Page(s): 1356-1366
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7967847&isnumber=8370013

22. Probability Calculation and Element Optimization of Probabilistic Hesitant Fuzzy Preference Relations Based on Expected Consistency
Author(s): W. Zhou and Z. Xu
Page(s): 1367-1378
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7967849&isnumber=8370013

23. Solving High-Order Uncertain Differential Equations via Runge–Kutta Method
Author(s): X. Ji and J. Zhou
Page(s): 1379-1386
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7967828&isnumber=8370013

24. On Non-commutative Residuated Lattices With Internal States
Author(s): B. Zhao and P. He
Page(s): 1387-1400
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7971990&isnumber=8370013

25. Robust ${L_1}$ Observer-Based Non-PDC Controller Design for Persistent Bounded Disturbed TS Fuzzy Systems
Author(s): N. Vafamand, M. H. Asemani and A. Khayatian
Page(s): 1401-1413
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7970135&isnumber=8370013

26. Decentralized Fault Detection for Affine T–S Fuzzy Large-Scale Systems With Quantized Measurements
Author(s): H. Wang and G. H. Yang
Page(s): 1414-1426
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7970193&isnumber=8370013

27. Convergence in Distribution for Uncertain Random Variables
Author(s): R. Gao and D. A. Ralescu
Page(s): 1427-1434
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7970195&isnumber=8370013

28. Line Integrals of Intuitionistic Fuzzy Calculus and Their Properties
Author(s): Z. Ai and Z. Xu
Page(s): 1435-1446
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7971962&isnumber=8370013

29. Unknown Input-Based Observer Synthesis for a Polynomial T–S Fuzzy Model System With Uncertainties
Author(s): V. P. Vu, W. J. Wang, H. C. Chen and J. M. Zurada
Page(s): 1447-1458
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7971977&isnumber=8370013

30. Distributed Filtering for Discrete-Time T–S Fuzzy Systems With Incomplete Measurements
Author(s): D. Zhang, S. K. Nguang, D. Srinivasan and L. Yu
Page(s): 1459-1471
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7972907&isnumber=8370013

31. Multi-ANFIS Model Based Synchronous Tracking Control of High-Speed Electric Multiple Unit
Author(s): H. Yang, Y. Fu and D. Wang
Page(s): 1472-1484
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7973097&isnumber=8370013

32. A New Self-Regulated Neuro-Fuzzy Framework for Classification of EEG Signals in Motor Imagery BCI
Author(s): A. Jafarifarmand, M. A. Badamchizadeh, S. Khanmohammadi, M. A. Nazari and B. M. Tazehkand
Page(s): 1485-1497
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7982748&isnumber=8370013

33. $Hinfty$ LMI-Based Observer Design for Nonlinear Systems via Takagi–Sugeno Models With Unmeasured Premise Variables
Author(s): T. M. Guerra, R. Márquez, A. Kruszewski and M. Bernal
Page(s): 1498-1509
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7982734&isnumber=8370013

34. Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections
Author(s): P. Rathore, J. C. Bezdek, S. M. Erfani, S. Rajasegarar and M. Palaniswami
Page(s): 1510-1524
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7984880&isnumber=8370013

35. Lattice-Valued Interval Operators and Its Induced Lattice-Valued Convex Structures
Author(s): B. Pang and Z. Y. Xiu
Page(s): 1525-1534
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7990263&isnumber=8370013

36. Deep Takagi–Sugeno–Kang Fuzzy Classifier With Shared Linguistic Fuzzy Rules
Author(s): Y. Zhang, H. Ishibuchi and S. Wang
Page(s): 1535-1549
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7984865&isnumber=8370013

37. Stability Analysis and Control of Two-Dimensional Fuzzy Systems With Directional Time-Varying Delays
Author(s): L. V. Hien and H. Trinh
Page(s): 1550-1564
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7987699&isnumber=8370013

38. A New Fuzzy Modeling Framework for Integrated Risk Prognosis and Therapy of Bladder Cancer Patients
Author(s): O. Obajemu, M. Mahfouf and J. W. F. Catto
Page(s): 1565-1577
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8000603&isnumber=8370013

39. Resolution Principle in Uncertain Random Environment
Author(s): X. Yang, J. Gao and Y. Ni
Page(s): 1578-1588
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8000682&isnumber=8370013

40. Observer-Based Fuzzy Adaptive Event-Triggered Control Codesign for a Class of Uncertain Nonlinear Systems
Author(s): Y. X. Li and G. H. Yang
Page(s): 1589-1599
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8002623&isnumber=8370013

41. Static Output Feedback Stabilization of Positive Polynomial Fuzzy Systems
Author(s): A. Meng, H. K. Lam, Y. Yu, X. Li and F. Liu
Page(s): 1600-1612
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8003337&isnumber=8370013

42. Global Asymptotic Model-Free Trajectory-Independent Tracking Control of an Uncertain Marine Vehicle: An Adaptive Universe-Based Fuzzy Control Approach
Author(s): N. Wang, S. F. Su, J. Yin, Z. Zheng and M. J. Er
Page(s): 1613-1625
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8003434&isnumber=8370013

43. Information Measures in the Intuitionistic Fuzzy Framework and Their Relationships
Author(s): S. Das, D. Guha and R. Mesiar
Page(s): 1626-1637
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8007288&isnumber=8370013

44. A Random Fuzzy Accelerated Degradation Model and Statistical Analysis
Author(s): X. Y. Li, J. P. Wu, H. G. Ma, X. Li and R. Kang
Page(s): 1638-1650
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8007272&isnumber=8370013

45. Measures of Probabilistic Interval-Valued Intuitionistic Hesitant Fuzzy Sets and the Application in Reducing Excessive Medical Examinations
Author(s): Y. Zhai, Z. Xu and H. Liao
Page(s): 1651-1670
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8010471&isnumber=8370013

46. A Unified Collaborative Multikernel Fuzzy Clustering for Multiview Data
Author(s): S. Zeng, X. Wang, H. Cui, C. Zheng and D. Feng
Page(s): 1671-1687
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8015177&isnumber=8370013

47. Asynchronous Piecewise Output-Feedback Control for Large-Scale Fuzzy Systems via Distributed Event-Triggering Schemes
Author(s): Z. Zhong, Y. Zhu and H. K. Lam
Page(s): 1688-1703
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8016371&isnumber=8370013

48. Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence
Author(s): N. Capuano, F. Chiclana, H. Fujita, E. Herrera-Viedma and V. Loia
Page(s): 1704-1718
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8016383&isnumber=8370013

49. Fuzzy Bayesian Learning
Author(s): I. Pan and D. Bester
Page(s): 1719-1731
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8017463&isnumber=8370013

50. Observer and Adaptive Fuzzy Control Design for Nonlinear Strict-Feedback Systems With Unknown Virtual Control Coefficients
Author(s): B. Chen, X. Liu and C. Lin
Page(s): 1732-1743
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8030110&isnumber=8370013

51. Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control
Author(s): B. Zhang, C. Yang, H. Zhu, P. Shi and W. Gui
Page(s): 1744-1756
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8039200&isnumber=8370013

52. Renewal Reward Process With Uncertain Interarrival Times and Random Rewards
Author(s): K. Yao and J. Zhou
Page(s): 1757-1762
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7954980&isnumber=8370013

53. Uncertainty Measures of Extended Hesitant Fuzzy Linguistic Term Sets
Author(s): C. Wei, R. M. Rodríguez and L. Martínez
Page(s): 1763-1768
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7970150&isnumber=8370013

54. Correction to “Detection of Resource Overload in Conditions of Project Ambiguity” [Aug 17 868-877]
Author(s): M. Pelikán, H. Štiková and I. Vrana
Page(s): 1769-1769
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8370173&isnumber=8370013

Call for Participation: IEEE World Congress on Computational Intelligence (IEEE WCCI 2018), Rio de Janeiro, Brazil (Jul 8-13)

The IEEE World Congress on Computational Intelligence (IEEE WCCI) is the largest technical event in the field of computational intelligence. The IEEE WCCI 2018 will host three conferences: The 2018 International Joint Conference on Neural Networks (IJCNN 2018), the 2018 IEEE International Conference on Fuzzy Systems (FUZZ- IEEE 2018), and the 2018 IEEE Congress on Evolutionary Computation (IEEE CEC 2018) under one roof. It encourages cross-fertilization of ideas among the three big areas and provides a forum for intellectuals from all over the world to discuss and present their research findings on computational intelligence.

IEEE WCCI 2018 will be held at the Windsor Barra Convention Centre, Rio de Janeiro, Brazil. Rio de Janeiro is a wonderful and cosmopolitan city, ideal for international meetings. Rio boasts fantastic weather, savory cuisine, hospitable people, and modern infrastructure. Rio is the first city to receive the Certificate of World Heritage for its Cultural Landscape, recently conferred by UNESCO.

IJCNN is the flagship conference of the IEEE Computational Intelligence Society and the International Neural Network Society. It covers a wide range of topics in the field of neural networks, from biological neural network modeling 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 a major event in the field of evolutionary computation, and covers all topics in evolutionary computation from theory to applications.

The highlights of the Congress include:

• 5 Keynotes by top-notch researchers – Miguel Nicolelis, Klaus-Robert Müller, Dario Floreano, Enrique Ruspini and Francisco Herrera (http://www.ecomp.poli.br/~wcci2018/speakers/);
• 15 Plenary speeches by world-renown scholars on pertinent and captivating topics within the technical scope of each conference;
• A public lecture by Gary Fogel;
• A few valuable and engaging panel sessions by revered researchers within the field of computational intelligence (http://www.ecomp.poli.br/~wcci2018/panel-sessions/);
• Over 20 tutorials covering a diverse range of topics offering a unique opportunity to disseminate in-depth information on specific topics in computational intelligence (http://www.ecomp.poli.br/~wcci2018/Tutorials/);
• A number of workshops to stimulate discussions between participants on active and emerging topics of computational intelligence (http://www.ecomp.poli.br/~wcci2018/workshops/);
• 115 special sessions organized by domain experts that are encompassed within the technical scope of the conference (http://www.ecomp.poli.br/~wcci2018/special-sessions/);
• 11 challenging and contemporary competitions offering distinctive topics in each track to cater to every participant’s needs (http://www.ecomp.poli.br/~wcci2018/competitions/).

Apart from the technical program, participants are also cordially invited to attend various social events that will include welcome reception and conference banquet. In addition, participants are also encouraged to explore the beautiful city of Rio de Janeiro which has an endless supply of attractions and things to see and do (http://www.ecomp.poli.br/~wcci2018/rio-de-janeiro-2/).

Call for Participation: International Summer Camp on AI, Hefei, China (Jul 1-14)

Artificial Intelligence (AI) has become an important engine for next ‘Cambrian of Civilization’, burst of knowledge and technology. Do you want to know the state of the arts of AI? Do you want to experience and touch by yourself the most advanced techniques of AI? Do you want to know the trend of AI in both academic and industry? Do you want to know all the above happened in China? Come to join us! This Summer Camp will bring you with excellent experience in both technology and culture. You may get some knowledge about why AI is so special in China, and why AIs in China are so special.

Further Information: http://scai.ustc.edu.cn/

CFP: Australasian Joint Conference on Artificial Intelligence (AI 2018) (Jul 1)

The Australasian Joint Conference on Artificial Intelligence is an annual conference that has dedicated to fostering research communication and collaboration among Australasian AI community since inception. The 31th Australasian Joint Conference on Artificial Intelligence will be hosted by Victoria University of Wellington, New Zealand in December 2018. The Program Committee invites prospective authors to submit original and previously unpublished research and application papers in all spectrums of Artificial Intelligence. The conference topics cover but are not limited to the following areas:

Prospective authors are invited to submit their original unpublished work to AI 2018. The topics of interest to this conference include but are not limited to the following:

• Agent-based and multiagent systems
• AI applications and innovations
• Cognitive modeling and computer human interaction
• Big data capture, representation, and analytics
• Commonsense reasoning
• Computer vision and image processing
• Constraint satisfaction, search and optimization
• Data mining and knowledge discovery
• Evolutionary computation and learning
• Fuzzy systems and neural networks
• Game playing and interactive entertainment
• Intelligent education and tutoring systems
• Knowledge acquisition and ontologies
• Knowledge representation and reasoning
• Machine learning and applications
• Multidisciplinary AI
• Natural language processing
• Planning and scheduling, combinatorial optimization
• Uncertainty in AI
• Visualisation in AI
• Robotics
• Game theory
• Text mining and Web mining
• Web/Social media mining

We encourage cross-boundary works contributing to theory and practice of AI. Novel application domains including cybersecurity, healthcare, IoT, social media and big data real-world applications are highly welcome. Submitted papers should not exceed 12 pages and should not be under review or submitted for publication elsewhere during the review period. All papers will be peer-reviewed by at least three independent referees.

All papers accepted and presented at AI 2018 will be included in the conference proceedings published by the Springer Lecture Notes in Computer Science/Artificial Intelligence (LNCS/LNAI, pending to approval), which are typically indexed by Engineering Index (Compendex), ISI Proceedings/ISTP, and DBLP.

Submission page is here.

Call for applications: IEEE CIS Scientific Mentoring Program 2018/2019

*** Description ***
The IEEE CIS Scientific Mentoring Program  is a service coordinated by the IEEE CIS Neural Network Technical Committee to support the research activity of IEEE CIS student members and young professionals. The Scientific Mentors can help IEEE CIS student members and young professionals by supporting their growth and guiding the steps in the field of Neural Networks and Learning Systems. This is a great opportunity for IEEE CIS student members and young professionals that can find in the Scientific Mentor a source of suggestions and feedbacks about the research.

*** Key aspects of the Scientific Mentoring Program ***
- Fixed time-horizon: 6 months
- Scope: support the research activity in the field of Neural Networks and Learning Systems
- Target: IEEE CIS Student Members and Young Professionals

*** Scientific Mentors for 2018/2019 ***
- Ivo Bukovsky, Professor, Czech Technical University in Prague, Czech Republic
- Catherine Huang, Senior Data Scientist, McAfee, USA
- Wei Lee Woon, Professor, Khalifa University, Abu Dhabi
- Marley Vellasco, Professor, Pontifícia Universidade Católica do Rio de Janeiro, Brasil

*** Procedure for the application ***
The applicant must send by email:
- A motivation letter (max 1 page)
- A short CV (max 1 page)
at the coordinator of the Scientific Mentoring Program for 2018/2019, Prof. Manuel Roveri, (manuel.roveri@polimi.it) by the submission deadline. The applicant could also suggest in the motivation letter one or two favorite mentors.

*** Important Dates ***
- Deadline for the submission of the application: September 30, 2018
- Notification:  October 20, 2018
- Mentoring Period: November 2018 - April 2019

*** Contacts ***
For further information about the Scientific Mentoring Program for 2018/2019, please contact Prof. Manuel Roveri, Politecnico di Milano, Italy, manuel.roveri@polimi.it

CFP: IEEE TEVC Special Issue on Theoretical Foundations of Evolutionary Computation (Oct 1)

I. AIM AND SCOPE

  Evolutionary computation (EC) methods such as evolutionary algorithms, ant colony optimization and artificial immune systems have been successfully applied to a wide range of problems. These include classical combinatorial optimization problems and a variety of continuous, discrete and mixed integer real-world optimization problems that are often hard to optimize by traditional methods (e.g., because they are non-linear, highly constrained, multi-objective, etc.). In contrast to the successful applications, there is still a need to understand the behaviour of these algorithms. The achievement and development of a solid theory of bio-inspired computation techniques is important as it provides sound knowledge on their working principles. In particular, it explains the success or the failure of these methods in practical applications. Theoretical analyses lead to the understanding of which problems are optimized (or approximated) efficiently by a given algorithm and which ones are not. The benefits of theoretical understanding for practitioners are threefold. 1) Aiding algorithm design, 2) guiding the choice of the best algorithm for the problem at hand and 3) determining optimal parameter settings.
   The aim of this special issue is to advance the theoretical understanding of evolutionary computation methods. We solicit novel, high quality scientific contributions on theoretical or foundational aspects of evolutionary computation. A successful exchange between theory and practice in evolutionary computation is very desirable and papers bridging theory and practice are of particular interest. In addition to strict mathematical investigations, experimental studies strengthening the theoretical foundations of evolutionary computation methods are very welcome. 

II. THEMES

This special issue will present novel results from different subareas of the theory of bio-inspired algorithms. The scope of this special issue includes (but is not limited to) the following topics: 

• Exact and approximation runtime analysis
• Black box complexity
• Self-adaptation
• Population dynamics
• Fitness landscape and problem difficulty analysis
• No free lunch theorems
• Theoretical Foundations of combining traditional optimization techniques with EC methods
• Statistical approaches for understanding the behaviour of bio-inspired heuristics
• Computational studies of a foundational nature

All classes of bio-inspired optimization algorithms will be considered including (but not limited to) evolutionary algorithms, ant colony optimization, artificial immune systems, particle swarm optimization, differential evolution, and estimation of distribution algorithms. All problem domains will be considered including discrete and continuous optimization, single-objective and multi-objective optimization, constraint handling, dynamic and stochastic optimization, co-evolution and evolutionary learning.

III. SUBMISSION

Manuscripts should be prepared according to the “Information for Authors” section of the journal found at http://ieee-cis.org/ pubs/tec/authors/ and submissions should be made through the journal submission website: http://mc.manuscriptcentral.com/tevc-ieee/, by selecting the Manuscript Type of “TFoEC Special Issue Papers” and clearly adding “TFoEC Special Issue Paper” to the comments to the Editor-in-Chief.

Submitted papers will be reviewed by at least three different expert reviewers. Submission of a manuscript implies that it is the authors’ original unpublished work and is not being submitted for possible publication elsewhere.

Each submission will contain at least one paragraph explaining why the paper is (potentially) relevant to practice.

IV. IMPORTANT DATES

• Submission open: February 1, 2018
• Submission deadline: October 1, 2018
• Tentative publication date: 2019

Papers will be assigned to reviewers as soon as they are submitted. Papers will be published online as soon as they are accepted.

For further information, please contact one of the following Guest Editors.

V. GUEST EDITORS

Pietro S. Oliveto

Department of Computer Science

University of Sheffield

United Kingdom

p.oliveto@sheffield.ac.uk

Anne Auger

INRIA

Ecole Polytechnique Paris

France

anne.auger@jnria.fr

Francisco Chicano

Department of Languages and Computing Sciences

University of Malaga Spain

chicano@lcc.uma.es

Carlos M. Fonseca

Department of Informatics Engineering

University of Coimbra Portugal

cmfonsec@dei.uc.pt

Call for Participation: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2018), Ottawa, Canada (Jun 12-14)

The IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2018) is dedicated to all aspects of computational intelligence, virtual environments and human-computer interaction technologies for measurement systems and related applications.

TOPICS OF INTEREST

Papers are solicited on all aspects of computational intelligence, human-computer interaction technologies, and virtual environments for measurement systems and the related applications, from the points of view of both theory and practice. This includes, but is not limited to, the following topics with specific emphasis on the measurement aspects:

• Intelligent Measurement Systems
• Human-computer Interaction
• Augmented & Virtual Reality
• Accuracy & Precision of Neural & Fuzzy Components
• Accuracy & Precision of Virtual Environments
• Perception, Neurodynamics, Neurophysiology, Psychophysics
• Multimodal Sensing
• Multimodal (Visual, Haptic, Audio, etc.) Virtual Environments
• Sensors & Displays
• Calibration and System Calibration
• Multi-Sensor Data Fusion & Intelligent Sensor Fusion
• Intelligent Monitoring & Control Systems
• Neural & Fuzzy Technologies For Identification, Prediction, & Control of Complex Dynamic Systems
• Evolutionary monitoring & control
• Evolutionary Techniques For Optimization & Logistics
• Neural & Fuzzy Signal/Image Processing For Industrial, Environmental & Domotic Applications
• Neural & Fuzzy Signal/Image Processing For Entertainment & Educational Applications
• Image Understanding & Recognition
• Machine & Deep Learning for Intelligent Systems
• Object Modeling
• Object & System Model Validation
• Virtual Reality languages
• Computational Intelligence Technologies For Robotics & Vision
• Computational Intelligence Technologies For Medical & Bioengineering Applications
• Computational Intelligence For Entertainment & Educational Applications
• Distributed Collaborative Virtual Environments
• Model-Based Telecommunications & Telecontrol Hybrid Systems
• Fuzzy & Neural Components For Embedded Systems
• Hardware Implementation of Neural & Fuzzy Systems For Measurements
• Neural, Fuzzy & Genetic/Evolutionary Algorithms For System Optimization & Calibration
• Neural & Fuzzy Techniques For System Diagnosis
• Reliability of Fuzzy & Neural Components
• Fault Tolerance & Testing In Fuzzy & Neural Components
• Neural & Fuzzy Techniques For Quality Measurement Standards
• Human Machine Interaction

ORGANIZERS

HONORARY CO-CHAIRS

Rafik Goubran - Carleton University, Canada

GENERAL CO-CHAIRS

Ana-Maria Cretu - Carleton University, Canada

Dalila Megherbi - University of Massachusetts Lowell, USA

PROGRAM CO-CHAIRS

Pierre Payeur -University of Ottawa, Canada

Sebastian Zug - Otto von Guericke University, Germany

Angelo Genovese - Università degli Studi di Milano, Italy

TUTORIALS & SPECIAL SESSION CHAIRS

Gabriel Wainer - Carleton University, Canada

LOCAL ARRANGEMENT CHAIR

Thiago Eustaquio Alves de Oliveira - University of Ottawa, Canada

Ghazal Rouhafzay - Carleton University, Canada