IEEE Symposium Series on Computational Intelligence 2009

2009 IEEE Workshop on Hybrid Intelligent Models and Applications

The International workshop will consist of papers describing research work that integrate different Computational Intelligence (CI) methodologies for the development of hybrid intelligent systems. CI methodologies at the moment include (at least) Neural Networks, Fuzzy Logic, Genetic Algorithms, Intelligent Agents, and Chaos Theory. The use of intelligent techniques, like neural networks, fuzzy logic and genetic algorithms, for real-world problems is now widely accepted. However, still the performance of any of these techniques can be improved, in many situations, by using them in conjunction with other techniques. For example, genetic algorithms can be used to optimize the design of a neural network for time series prediction, or fuzzy logic can be used to combine the information from expert neural modules, just to mention two cases. Also, mathematical methods, like the ones from Chaos and Fractal Theory, can be used in conjunction with intelligent techniques to improve the performance of hybrid systems for real-world applications. The international workshop will consist of papers addressing these hybrid approaches and similar ones, either theoretically or for real-world applications. The workshop is intended primarily for researchers and graduate students working on these research areas.
The main topics of interest are:

1. Successful new applications to real-world problems of Hybrid Intelligent Systems (HIS) that are found to achieve better results than conventional techniques. In this case, special attention should be given to the metrics used to compare HIS techniques with conventional ones.
2. Developments of innovative hybrid methods combining CI techniques and conventional techniques. In this case, the problems to be considered in these papers may not be as complex as the ones in the previous point, but the authors have to explain very carefully how their proposed method could be used, in the future, to solve real-world problems.
3. Papers considering original research on new HIS architectures, models or techniques, in this case authors would have to make a detailed description of how their proposed approach is compared with other related approaches.

Specifically the workshop will focus on, but not limited to, the following topics:

• Genetic Algorithm for Fuzzy System Optimization
• Genetic Algorithms for Neural Network Optimization
• Neuro-Fuzzy-Genetic Approaches
• Hybrid Intelligent Systems for Pattern Recognition
• Hybrid Modular Neural Networks
• Neuro-Fuzzy Models and Applications
• Genetic Algorithms for Hybrid Intelligent Systems Design
• Genetic Fuzzy Systems
• Genetic Neural Systems
• Hybrid Evolutionary Algorithms
• Ant Colony for Neural Network Optimization
• Type-2 Fuzzy Logic in Neural Networks Design
• Type-2 Fuzzy Logic in Evolutionary Algorithms
• Chaos Theory in Genetic Algorithms

Program Chair:
Patricia Melin, Tijuana Institute of Technology, Mexico

Program Committee:
Oscar Castillo, Tijuana Institute of Technology, Mexico
Roseli A. Francelin Romero, University of Sao Paulo, Brazil
Eduardo Gomez-Ramirez, La Salle University, Mexico
Kaoru Hirota, Tokyo Institute of Technology, Japan
Janusz Kacprzyck, Polish Academy of Sciences, Poland
Nadia Nedjah, State University of Rio de Janeiro, Brazil
Witold Pedrycz, University of Alberta, Canada
Edgar Sanchez, CINVESTAV, Guadalajara, Mexico
Ronald R. Yager, Iona College, USA
Vladik Kreinovich, University of Texas, El Paso, USA
Jacek Zurada, University of Louisville, USA