CFP: WCCI Special session on Computational Intelligence for Energy Storage Systems Modeling and Management

2018 IEEE World Congress on Computational Intelligence (WCCI 2018)
Rio de Janeiro, BRAZIL, 08-13 July 2018 - http://www.ecomp.poli.br/~wcci2018/

Abstract & Topics

Energy Storage Systems (ESS)s have become widely pervasive in several sectors, both in the civil and in the industrial engineering fields. Among the several applications, the most critical ones regard the storing of energy in the future Smart Grids and microgrids, and the power sourcing for Electric and Hybrid Vehicles. In this context, the management of the ESS represents a crucial task in order to guarantee efficient, effective and robust energy storing. In order to achieve a safe and reliable usage of ESSs, it is important to synthesize suitable models capable to predict the cell behavior in order to avoid damages, to estimate the State of Charge (SoC) and the State of Health (SoH), and to perform the cells equalization. Moreover, the design of efficient and effective algorithms for optimal energy flows routing in Smart Girds and microgrids is a challenging task, especially in presence of ESSs. Computational intelligence techniques represent a powerful approach to face the above-mentioned tasks, allowing to deal with the strong nonlinear and dynamic behavior of electrochemical cells, as well as to design Energy Management Systems (EMS) able to cope with nonlinear and time variant systems, such as microgrids and Smart Grids, especially in presence of stochastic renewable energy sources.

Topics of interest include (but are not limited to) applications of Computational Intelligence techniques (Neural networks and Machine Learning, Evolutionary Optimization and Fuzzy Systems) to the following problems:

-       ESS modeling
- ESS parameters identification
-       ESS state of charge estimation
- ESS state of health estimation
-       ESS cell balancing
-       Neural Networks for non-linear system identification
-       EMS design for Smart Grids and micro grids in presence of ESSs
- EMS in hybrid and electric vehicles
-       EMS in Smart Buildings
-       Computational Intelligence techniques for complex systems modeling

Organizers

Prof. Fabio M. Frattale Mascioli, University of Rome “La Sapienza”, Rome, fabio.mascioli@pomos.it
Prof. Antonello Rizzi, University of Rome “La Sapienza”, Rome, antonello.rizzi@uniroma1.it
Dr. Maurizio Paschero University of Rome “La Sapienza”, Rome, maurizio.paschero@uniroma1.it


Fabio Massimo Frattale Mascioli

Prof. Fabio Massimo Frattale Mascioli received his MS and PhD in Information and Communication Engineering in 1989 and 1995, from the University "La Sapienza" of Rome. In 1996, he joined the DIET Department of the University "La Sapienza" of Rome as Assistant Professor. He was promoted to Associate Professor of Circuit Theory in 2000 and to Full Professor in 2011. His research interest mainly regards neural networks and neuro-fuzzy systems and their applications to clustering, classification and function approximation problems, circuit modeling for vibration damping, energy conversion systems and electric and hybrid vehicles. He is author or co-author of more than 150 papers. Since 2007, he serves as scientific director of the `Polo per la Mobilità Sostenibile' (POMOS) Laboratories, DIET Department.

Antonello Rizzi

Antonello Rizzi received the Ph.D. in Information and Communication Engineering in 2000, from the University of Rome “La Sapienza”. In September 2000, he joined the INFO-COM Dpt., as an Assistant Professor. Since July 2010 he joined the “Information Engineering, Electronics and Telecommunications” Dpt. (DIET), in the same University. His major research interests are in the area of Soft Computing, Pattern Recognition and Computational Intelligence, including supervised and unsupervised data driven modeling techniques, neural networks, fuzzy systems and evolutionary algorithms. His research activity concerns the design of automatic modeling systems, focusing on classification, clustering, function approximation and prediction problems. Currently, he is working on different research topics and projects, such as Granular Computing, Data Mining and Knowledge Discovery, Content Based Retrieval Systems, classification and clustering systems for structured patterns, graph and sequence matching, agent-based clustering, smart grids and micro-grids modeling and control, intelligent systems for sustainable mobility, battery management systems. Since 2008, he serves as the scientific coordinator and technical director of the R&D activities in the "Intelligent Systems Laboratory" within the Research and Technology Transfer Center for Sustainable Mobility of Lazio Region. He is the scientific coordinator of the "Computational Intelligence and Pervasive Systems" Lab at DIET. Dr. Rizzi (co-)authored more than 140 international journal/conference papers and book chapters. He is a member of IEEE.

Maurizio Paschero

Maurizio Paschero is a post-doctoral research associate at the Information Engineering, Electronics and Telecommunications Department of the University of Rome "La Sapienza" since September 2008, where he works in the Polo per la Mobilià Sostenibile (POMOS) Laboratories.
He received his M.S in Electronic Engineering 2003 and the Ph.D in Information and Communication Engineering in 2006 from the University "La Sapienza" of Rome and the Ph.D in Mechanical Engineering in 2008 from Virginia Polytechnic Institute and State University.
His major fields of interest include Soft computing, Smart Grids, multi-physic circuital modeling, intelligent signal processing, and battery modeling. He is author or more than 40 scientific publications on international journals and conferences.

Authors’ Information

Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of WCCI 2018.
Authors who submit papers to this session are invited to mention it in the form during the submission.
Submissions to Regular and Special Sessions follow identical format, instructions, deadlines and procedures of the other papers.

More information can be found at

Official WCCI 2018 Call for Papers:
http://www.ecomp.poli.br/~wcci2018/call-for-papers/

Official WCCI 2018 Guidelines: http://www.ecomp.polbr/i.~wcci2018/submissions/#guidelines

The Special Session website:
https://sites.google.com/a/uniroma1.it/wcc2018-ci4essmm/

Important Dates

Paper Submission Deadline: 15 January 2018
Notification of Acceptance: 15 March 2018
Early Registration:         1 May 2018
WCCI 2018 Conference: 8 – 13 July 2018

Webinar: Decomposition Based Multiobjective Evolutionary Computation

Speaker: Prof. Qingfu Zhang, Department of Computer Science, City University of Hong Kong qingfu.zhang@cityu.edu.hk

Time: 11am-12pm (GMT), Dec 18, 2017

Abstract

Multiobjective Evolutionary Computation has been a major research topic in the field of evolutionary computation for many years. It has been generally accepted that combination of evolutionary algorithms and traditional optimization methods should be a next generation multiobjective optimization solver. Decomposition methods have been well used and studied in traditional multiobjective optimization. In this talk, I will describe MOEA/D algorithmic framework. MOEA/D decomposes a multiobjective problem into a number of subtasks, and then solves them in a collaborative manner.  MOEA/D provides a very natural bridge between multiobjective evolutionary algorithms and traditional decomposition methods. It has been a commonly used evolutionary algorithmic framework in recent years. I will explain the basic ideas behind MOEA/D and some recent developments.   I will also outline some possible research issues in multiobjective evolutionary computation. 

Bio

Prof. Qingfu Zhang is a Professor at the Department of Computer Science, City University of Hong Kong, Hong Kong. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications.  He is currently leading the Metaheuristic Optimization Research Group in City University of Hong Kong.  MOEA/D, a multiobjective optimization algorithmic framework, developed in his group, is one of the most widely used and researched multiobjective evolutionary algorithmic framework.

Dr. Zhang is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the IEEE Transactions on Cybernetics. He is also an Editorial Board Member of three other international journals.  He was awarded the 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award.  He is a 2016 and 2017 highly cited researcher in Computer Science (Clarivate Analytics) and an IEEE fellow.  He was selected in the 1000 talents program in China in 2015. He was a Changjiang visiting chair professor with Xidian University, China from 2011 to 2014.

Registration on GoToWebinar: https://attendee.gotowebinar.com/register/672887209381227778

CFP: CEC 2018 Special Session on “Evolutionary Computation in Healthcare Industry”

Jul 8-13, 2018, Rio de Janeiro, BRAZIL

We proposed a special session on “Evolutionary Computation in Healthcare Industry” in IEEE IEEE Congress on Evolutionary Computation 2018 (CEC 2018). Please consider to contribute to and/or forward to the appropriate groups the following opportunity to publish original research articles in CEC 2018.

https://sites.google.com/view/ieee-cis-tf-ish/cec-2018-special-session-on-evolutionary-computation-in-healthcare-industry

Call for Papers

Summary of the special session:

Worldwide, the healthcare industry would continue to thrive and grow, because diagnosis, treatment, disease prevention, medicine, and service affect the mortal rates and life quality of human beings. Two key issues of the modern healthcare industry are improving healthcare quality as well as reducing economic and human costs. The problems in the healthcare industry can be formulated as scheduling, planning, predicting, and optimization problems, where evolutionary computation methods can play an important role. Although evolutionary computation has been applied to scheduling and planning for trauma system and pharmaceutical manufacturing, other problems in the healthcare industry like decision making in computer-aided diagnosis and predicting for disease prevention have not properly formulated for evolutionary computation techniques, and many evolutionary computation techniques are not well-known to the healthcare community. This special session aims to promote the research on evolutionary computation methods for their application to the healthcare industry.

Scope and Topics:

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

• Evolutionary computation in resource allocation for hospital location planning, aeromedical retrieval system planning, etc.

• Application of evolutionary computation for job scheduling, such as ambulance scheduling, nurse scheduling, job scheduling in medical device and pharmaceutical manufacturing, etc.

• Multiple-criteria decision-making for computer-aided diagnosis using expert systems.

• Web self-diagnostic system with the application of information retrieval and recommendation system.

• Learning and optimization for vaccine selection and personalized/stratified medicine.

• Data-driven surrogate-assisted evolutionary algorithms in pharmaceutical manufacturing processes.

• Modeling and prediction in epidemic surveillance system for disease prevention.

• Route planning for disability robots.

Important Dates:

-Paper submission: 15th January, 2018

-Notification to authors: 15th March, 2018

-Final submission: 1st May, 2018

-Early registration: 1st May, 2018

Organizers:

Handing Wang, Department of Computer Science, University of Surrey, UK

Rong Qu, School of Computer Science, University of Nottingham, UK

Dujuan Wang, College of Transportation Management, Dalian Maritime University, China

Yaochu Jin, Department of Computer Science, University of Surrey, UK

CFP: WCCI 2018 Special Session: Computational Intelligence for the Automated Design of Machine Learning and Search (CIAD 2018)

http://titancs.ukzn.ac.za/WCCI2018SpecialSession.aspx

Aims, Scope and List of Topics:

Machine learning and search algorithms play an imperative role in solving real world problems in industry and business sectors. Systems employing these techniques have contributed to many facets of industry including data mining, transportation, health systems, computer vision, computer security, robotics, software engineering and scheduling amongst others. These systems employ one or more techniques such as neural networks, fuzzy logic, evolutionary algorithms, multi-agent approaches and rule-based systems. Implementation of these techniques require a number of design decisions to be made, e.g. what architecture to use, what parameter values to use, and derivation of problem specific operators. It may also be necessary to employ a hybrid system combining techniques to solve a problem which introduces additional decisions such as which techniques to use and how to combine these techniques. This makes the development of computational systems time consuming, requiring many person-hours. Consequently, there have been a number of initiatives to automate these processes using computational intelligence.

There has been a fair amount of research into parameter tuning and control. The field of auto-ML aims to automate the design of machine learning algorithms so as to produce off-the-shelf machine learning techniques. Attempts to automate neural network architecture design has led to the field of neuroevolution. Research in this area has also been directed at inducing fuzzy functions, rule-based systems and multi-agent architectures. Hyper-heuristics, which were initially aimed at providing generalized solutions to combinatorial optimization problems, are shown to be effective in the automated design of search techniques. Evolutionary algorithms such as genetic programming and genetic algorithms have made a valuable contribution to this field. The aim of this special session is to examine and promote recent developments in the field and future directions including the challenges and how these can be overcome.

The topics covered include, but are not limited to the following:

* Architecture design, e.g. design of neural networks and multi-agent architectures
* Automated hybridization of intelligent techniques
* Auto-ML
* Automatic programming
* Derivation of constructive heuristics
* Derivation of evaluation functions
* Derivation of operators
* Explainable machine learning
* Hyper-heuristics
* Neuroevolution
* Parameter control and tuning
* Search-based software engineering
* Self*-search

Organizers:

Nelishia Pillay,
University of Pretoria, South Africa
E-mail: npillay@cs.up.ac.za

Rong Qu,
University of Nottingham, UK
E-mail: Rong.Qu@nottingham.ac.uk

Important Dates:

Paper submission deadline: 15 January, 2018
Paper acceptance notification: 15 March, 2018
Final paper submission deadline: 1 May, 2018
Early registration: 1 May, 2018

Paper Submission:

Special session papers are treated the same as regular papers and must be submitted via the WCCI 2018 submission website. When submitting choose the " Computational Intelligence for the Automated Design of Machine Learning and Search " special session from the "Main Research Topic" list.

Webinar: Bridge: a New Challenge for AI? – Véronique Ventos (Nov 20)

1. Mon, Nov 20, 2017 4:00 PM - 5:00 PM GMT

Speaker

Dr. Veronique Ventos, Associate Professor, University Paris Saclay Abstract

Games have always been an excellent field of experimentation for the nascent techniques in computer science and in different areas of Artificial Intelligence including Machine Learning. Despite their complexity, game problems are much easier to understand and to model than real life problems. Systems initially designed for games are then used in the context of real applications. In the last decades, designs of champion-level systems dedicated to a game (game AI) were considered as milestones of computer science and AI.
The first part of the webinar is devoted to the presentation of the different aspects of bridge and of various challenges inherent to it.
In a second part, we will present our work concerning the optimization of the AI Wbridge5 developed by Yves Costel. This work is based on a recent seed methodology which optimizes the quality of Monte-Carlo simulations and which has been defined and validated in other games. The Wbridge5 version boosted with this method won the World Computer-Bridge Championship twice, in September 2016 and in August 2017.
Finally, the last part is about various ongoing works related to the design of a hybrid architecture entirely dedicated to bridge using recent numeric and symbolic Machine Learning modules. Biography

PhD in Artificial Intelligence (Knowledge Representation and Machine Learning) in 1997. Associate professor at University Paris Saclay, France since 1998. Before joining in 2015 the group A&O in the interplay of Machine Learning and Optimization, she worked in the group LaHDAK (Large-scale Heterogeneous DAta and Knowledge) at Laboratory of Computer Science (LRI). She started playing bridge in 2004 and is now 59th French woman player out of 48644 players. In 2015, she set up the AlphaBridge project combining her two passions. AlphaBridge is dedicated to solve the game of bridge by defining a hybrid architecture including recent numeric and symbolic ML modules.


Register at: https://register.gotowebinar.com/register/6958887543473419777

CFP: IEEE World Congress on Computational Intelligence (WCCI 2018) (Jan 15, 2018)

http://www.ecomp.poli.br/~wcci2018/

Call for Papers

On behalf of the IEEE WCCI 2018 Organizing Committee, it is our great pleasure to invite you to the bi-annual IEEE World Congress on Computational Intelligence (IEEE WCCI), which 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 – co-sponsored by International Neural Network Society – INNS), 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 Convention Centre, Rio de Janeiro, Brazil. Rio de Janeiro is one of the most attractive cities in South America, with the largest urban forest in the world, beautiful bays, lagoons and 90 kms of beaches and mountains. Known as one of the most beautiful cities in the World, Rio de Janeiro is the first city to receive the certificate of World Heritage for its Cultural Landscape. This unprecedented title was recently conferred by the United Nations Educational, Cultural and Scientific Organization (UNESCO).

Rio de Janeiro is easily accessible from all over the world, with direct flights from major cities in North America, Europe, Africa and Middle East. It is also a one stop away from Asia and Australia. The venue, The Windsor Barra Complex, features a brand new Convention Center and three different categories hotels, in the fastest growing region in Rio de Janeiro, with walking distance from a great choice of restaurants and shopping centers.

IEEE Computational Intelligence Society has maintained its position as a leader of journals in computational intelligence. CIS journals sustained their status as premier scholarly publications, earning high rankings in the Journal Citation Report by Thomson Reuters.

• IEEE Transactions on Neural Networks and Learning Systems (IF: 4.854)
• IEEE Transactions on Fuzzy Systems (IF: 6.701)
• IEEE Transactions on Evolutionary Computation (IF: 5.908)
• IEEE Computational Intelligence Magazine (IF: 3.647)

List of topics:

IEEE CEC

• Algorithms
  • Ant colony optimization
  • Artificial immune systems
  • Coevolutionary systems
  • Cultural algorithms
  • Differential evolution
  • Estimation of distribution algorithms
  • Evolutionary programming
  • Evolution strategies
  • Genetic algorithms
  • Genetic programming
  • Heuristics, metaheuristics and hyper-heuristics
  • Interactive evolutionary computation
  • Learning classifier systems
  • Memetic, multi-meme and hybrid algorithms
  • Molecular and quantum computing
  • Multi-objective evolutionary algorithms
  • Parallel and distributed algorithms
  • Particle swarm optimization
• Theory and Implementation
  • Adaptive dynamic programming and reinforcement learning
  • Autonomous mental development
  • Coevolution and collective behavior
  • Convergence, scalability and complexity analysis
  • Evolutionary computation theory
  • Representation and operators
  • Self-adaptation in evolutionary computation
• Optimization
  • Numerical optimization
  • Discrete and combinatorial optimization
  • Multiobjective optimization
• Handling of Various Aspects
  • Large-scale problems
  • Preference handling
  • Evolutionary simulation-based optimization
  • Meta-modeling and surrogate models
  • Dynamic and uncertain environments
  • Constraint and uncertainty handling

• Hybrid Systems of Computational Intelligence
  • Evolved neural networks
  • Evolutionary fuzzy systems
  • Evolved neuro-fuzzy systems
• Related Areas and Applications
  • Art and music
  • Artificial ecology and artificial life
  • Autonomous mental and behavior development
  • Biometrics, bioinformatics and biomedical applications
  • Classification, clustering and data analysis
  • Data mining
  • Defense and cyber security
  • Evolutionary games and multi-agent systems
  • Evolvable hardware and software
  • Evolutionary Robotics
  • Engineering applications
  • Emergent technologies
  • Finance and economics
  • Games
  • Intelligent systems applications
  • Robotics
  • Real-world applications
  • Emerging areas

IJCNN

• NEURAL NETWORK MODELS
  • Feedforward neural networks
  • Recurrent neural networks
  • Self-organizing maps
  • Radial basis function networks
  • Attractor neural networks and associative memory
  • Modular networks
  • Fuzzy neural networks
  • Spiking neural networks
  • Reservoir networks (echo-state networks, liquid-state machines, etc.)
  • Large-scale neural networks
  • Learning vector quantization
  • Deep neural networks
  • Randomized neural networks
  • Other topics in artificial neural networks
• MACHINE LEARNING
  • Supervised learning
  • Unsupervised learning and clustering, (including PCA, and ICA)
  • Reinforcement learning and adaptive dynamic programming
  • Semi-supervised learning
  • Online learning
  • Probabilistic and information-theoretic methods
  • Support vector machines and kernel methods
  • EM algorithms
  • Mixture models, ensemble learning, and other meta-learning or committee algorithms
  • Bayesian, belief, causal, and semantic networks
  • Statistical and pattern recognition algorithms
  • Sparse coding and models
  • Visualization of data
  • Feature selection, extraction, and aggregation
  • Evolutionary learning
  • Hybrid learning methods
  • Computational power of neural networks
  • Deep learning
  • Other topics in machine learning
• NEURODYNAMICS
  • Dynamical models of spiking neurons
  • Synchronization and temporal correlation in neural networks
  • Dynamics of neural systems
  • Chaotic neural networks
  • Dynamics of analog networks
  • Itinerant dynamics in neural systems
  • Neural oscillators and oscillator networks
  • Dynamics of attractor networks
  • Other topics in neurodynamics
• COMPUTATIONAL NEUROSCIENCE
  • Connectomics
  • Models of large-scale networks in the nervous system
  • Models of neurons and local circuits
  • Models of synaptic learning and synaptic dynamics
  • Models of neuromodulation
  • Brain imaging
  • Analysis of neurophysiological and neuroanatomical data
  • Cognitive neuroscience
  • Models of neural development
  • Models of neurochemical processes
  • Neuroinformatics
  • Other topics in computational neuroscience
• NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION
  • Neurocognitive networks
  • Cognitive architectures
  • Models of conditioning, reward and behavior
  • Cognitive models of decision-making
  • Embodied cognition
  • Cognitive agents
  • Multi-agent models of group cognition
  • Developmental and evolutionary models of cognition
  • Visual system
  • Auditory system
  • Olfactory system
  • Other sensory systems
  • Attention
  • Learning and memory
  • Spatial cognition, representation and navigation
  • Semantic cognition and language
  • Grounding, symbol grounding
  • Neural models of symbolic processing
  • Reasoning and problem-solving
  • Working memory and cognitive control
  • Emotion and motivation
  • Motor control and action
  • Dynamical models of coordination and behavior
  • Consciousness and awareness
  • Models of sleep and diurnal rhythms
  • Mental disorders
  • Other topics in neural models of perception, cognition and action
• NEUROENGINEERING
  • Brain-machine interfaces
  • Neural prostheses
  • Neuromorphic hardware
  • Embedded neural systems
  • Other topics in neuroengineering
• BIO-INSPIRED AND BIOMORPHIC SYSTEMS
  • Brain-inspired cognitive architectures
  • Embodied robotics
  • Evolutionary robotics
  • Developmental robotics
  • Computational models of development
  • Collective intelligence
  • Swarms
  • Autonomous complex systems
  • Self-configuring systems
  • Self-healing systems
  • Self-aware systems
  • Emotional computation
  • Artificial life
  • Other topics in bio-inspired and biomorphic systems
• APPLICATIONS 
  • Applications of deep neural networks
  • Bioinformatics
  • Biomedical engineering
  • Data analysis and pattern recognition
  • Speech recognition and speech production
  • Robotics
  • Neurocontrol
  • Approximate dynamic programming, adaptive critics, and Markov decision processes
  • Neural network approaches to optimization
  • Signal processing, image processing, and multi-media
  • Temporal data analysis, prediction, and forecasting; time series analysis
  • Communications and computer networks
  • Data mining and knowledge discovery
  • Power system applications
  • Financial engineering applications
  • Security applications
  • Applications in multi-agent systems and social computing
  • Manufacturing and industrial applications
  • Expert systems
  • Clinical applications
  • Big data applications
  • Other applications
  • Smart grid applications
• CROSS-DISCIPLINARY TOPICS 
  • Hybrid intelligent systems
  • Swarm intelligence
  • Sensor networks
  • Quantum computation
  • Computational biology
  • Molecular and DNA computation
  • Computation in tissues and cells
  • Artificial immune systems
  • Philosophical issues
  • Other cross-disciplinary topics

FUZZ-IEEE

• Mathematical and theoretical foundations
  • fuzzy measures and fuzzy integrals
  • fuzzy differential equations
  • fuzzy logic, fuzzy inference systems
  • aggregation, operators, fuzzy relations
• Fuzzy control
  • optimal control of dynamic systems
  • adaptive and dynamically evolving process control
  • networked control systems
  • plantwide, monitoring, and supervisory control
• Robotics and autonomous systems
  • navigation
  • decision making and situation awareness
  • handling systems
  • automated factories
  • smart industry
• Fuzzy hardware, software, sensors, actuators, architectures
• Fuzzy data and analysis
  • clustering, classification and pattern recognition
  • statistics and imprecise probabilities
  • data summarization
  • big data
  • time series modeling and forecasting
  • data analytics and visualization
  • social networks mining and analysis
• Data management and web engineering
  • fuzzy data modeling
  • databases and information retrieval
  • data aggregation and fusion
  • fuzzy markup languages
• Granular computing
  • type-2 fuzzy sets
  • intuitionistic fuzzy sets
  • higher order fuzzy sets
  • interval data processing
  • rough sets and relations
  • hybrid granular approaches
  • data clouds

• Computational and artificial intelligence
  • fuzzy neural networks
  • fuzzy deep learning
  • fuzzy evolutionary algorithms
  • dynamically evolving fuzzy systems
  • fuzzy agent systems
  • knowledge representation and approximate reasoning
  • elicitation of fuzzy sets
  • explainable artificial intelligence
• Otimization and operations research
  • fuzzy mathematical programming
  • possibilistic optimization
  • fuzzy algorithms and heuristic search
• Decision analysis, multi-criteria decision making, and decision support
• Fuzzy modeling, identification, and fault detection
• Knowledge discovery
• Fuzzy image, speech and signal processing, vision and multimedia data
• Linguistic summarization, natural language processing
• Applications
• industry, technology, engineering
• finance, business, economics
• medicine, biological and social sciences
• geographical information systems
• social and communication networks
• agriculture and environment engineering
• security and mobility

Important Dates

• 15 December 2017 – Tutorial, Special Sessions, Workshop and Competition Proposals
• 15th January 2018 – Paper Submission 
• 15th March 2018 – Paper Acceptance
• 1st May 2018 – Final Paper Submission
• 1st May 2018 – Early Registration
• 8-13 July 2018 – IEEE WCCI 2018, Rio de Janeiro, Brazil