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Introduction

Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models.

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Important date

2016-09-20
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Submission Topics

  • Rough set theory and applications
  • Fuzzy set theory and applications
  • Fuzzy-rough, rough-fuzzy and beyond
  • Approximate and uncertain reasoning
  • Case-based reasoning
  • Computing with words
  • Evolutionary computing
  • Natural Computing
  • Affective Computing
  • Multi-agent systems
  • Multi-criteria decision support
  • Neural networks
  • Neuro-fuzzy
  • Neuro-evolutionary systems
  • Non-classical logic
  • Pattern recognition and image processing
  • RBF structures
  • Self-organizing networks
  • Support vector machines and kernel methods
  • Bayesian models and statistical machine learning
  • Cognitive and neural robotics.
  • Data mining and knowledge discovery.
  • Signal processing and speech analysis.
  • Image processing and machine vision.
  • Human-centric computer interfaces (BCI, etc.).
  • Neuroinformatics and bioinformatics.
  • Fuzzy logic and fuzzy set theory
  • Lattice theory and multi-valued logic
  • Type-2 fuzzy logic
  • Rough sets and random sets
  • Fuzzy measure and integral
  • Possibility theory and imprecise probability
  • Fuzzy preference modeling
  • Granular computing
  • Fuzzy systems for natural language processing
  • Fuzzy information processing
  • Fuzzy systems modelling and identification
  • Fuzzy control and intelligent systems
  • Fuzzy clustering
  • Evolutionary fuzzy systems
  • Evolved neuro-fuzzy systems
  • Hybrid fuzzy systems
  • Ant colony optimization
  • Artificial immune systems
  • Cultural algorithms
  • Genetic algorithms
  • Genetic programming
  • Interactive evolutionary computation
  • Multi-objective evolutionary algorithms
  • Particle swarm optimization
  • Reinforcement learning
  • Self-adaptation in evolutionary computation
  • Multiobjective optimization
  • Evolved neural networks
  • Artificial ecology and artificial life
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