Invited Speakers

 

 

Title: Optimization of modular granular neural networks using bio-inspired optimization algorithms with fuzzy parameter adaptation for human recognition

Melin, Patricia Spearker: Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico

Abstract: In this talk, new models of modular neural networks optimized with bio-inspired optimization algorithms using fuzzy parameter adaptation are proposed. The models use a granular approach based on analyzing database complexity. In this case the proposed method is tested with the problem of human recognition based on face information. The ORL and the ESSEX face databases are used to test the effectiveness of the proposed method. To compare with other related works using the same databases, four cases are established (3 for the ESSEX Database and 1 for the ORL Database). The results using the proposed method are better than the results achieved by other works, and this affirmation is based on a statistical comparison of results. The main idea is to design the architectures of modular neural networks using bio-inspired optimization methods, such as particle swarm optimization, grey wolf optimization and the firefly algorithm. The distribution of persons in each granule is determined by an initial analysis, resulting in a grouping of data with the same complexity. The proposed method allows the optimization of multiple modular neural networks that use different sizes of data sets for the training phase, which means that multiple results can be obtained.

Biography: Prof. Patricia Melin holds the Doctor in Science degree (Doctor Habilitatus D.Sc.) in Computer Science from the Polish Academy of Sciences (with the Dissertation “Hybrid Intelligent Systems for Pattern Recognition using Soft Computing”). She is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico, since 1998. In addition, she is serving as Director of Graduate Studies in Computer Science and head of the research group on Hybrid Neural Intelligent Systems (2000-present). Currently, she is President of NAFIPS (North American Fuzzy Information Processing Society). Prof. Melin is the founding Chair of the Mexican Chapter of the IEEE Computational Intelligence Society. She is member of the IEEE Neural Network Technical Committee (2007 to present), the IEEE Fuzzy System Technical Committee (2014 to present) and in Chair of the Task Force on Hybrid Intelligent Systems (2007 to present) and she is currently Associate Editor of the Journal of Information Sciences and IEEE Transactions on Fuzzy Systems. She is member of NAFIPS, IFSA, and IEEE. She belongs to the Mexican Research System with level III. Her research interests are in Modular Neural Networks, Type-2 Fuzzy Logic, Pattern Recognition, Fuzzy Control, Neuro-Fuzzy and Genetic-Fuzzy hybrid approaches. She has published over 220 journal papers, 10 authored books, 20 edited books, and more than 250 papers in conference proceedings with h-index of 42. She has served as Guest Editor of several Special Issues in the past, in journals like: Applied Soft Computing, Intelligent Systems, Information Sciences, Non-Linear Studies, JAMRIS, Fuzzy Sets and Systems, and Engineering Letters.