Professor Hidehiko Okada

Area and Subject Taught User Interface
Research Theme(s) Computational Intelligence
Academic Degrees Doctor of Engineering, Osaka Prefecture University
Keywords for Research Field Genetic Algorithm, Neural Network, Fuzzy Theory
Office Phone Number Not Public
e-mail

Research Overview

The aim of this research is to develop methods for improving and extending evolutionary algorithms including genetic algorithm, applying evolutionary algorithms to learning of neural networks and fuzzy systems.

Notable Publications and Works in the Last Three Years

  1. H. Okada: Evolution of Fuzzy Neural Networks Using an Evolution Strategy with Fuzzy Genotype Values, World Academy of Science, Engineering and Technology, Vol.9, No.4, pp.296-303, (2015.09)
  2. H. Okada: Fuzzy Particle Swarm Optimization Applied to Neuroevolution, Proc. of the Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS & ISIS 2014), pp.1595-1596 (2014.12)
  3. H. Okada: Evolving Fuzzy Neural Networks by Particle Swarm Optimization with Fuzzy Genotype Values, International Journal of Computing and Digital Systems, Vol.3, No.3, pp.181-187 (2014.09)
  4. H. Okada: Comparison of Two Interval Models for Fuzzy-valued Genetic Algorithm, in Y. Suzuki and M. Hagiya (eds): Recent Advances in Natural Computing, Springer, Chapter 2, pp.23-34, (2014.08) ISBN 978-4-431-55104-1
  5. H. Okada: Genetic Algorithm with Fuzzy Genotype Values and Its Application to Neuroevolution, International Journal of Computer, Information Science and Engineering, Vol.8, No.1, pp.1-7 (2014.01)