Cooperation of Bio-inspired and Evolutionary Algorithms for Neural Network Design

Abstract

A meta-heuristic called Co-Operation of Biology-Related Algorithms (COBRA) with a fuzzy controller, as well as a new algorithm based on the cooperation of Differential Evolution and Particle Swarm Optimization (DE+PSO) and developed for solving real-valued optimization problems, were applied to the design of artificial neural networks. The usefulness and workability of both meta-heuristic approaches were demonstrated on various benchmarks. The neural network’s weight coefficients represented as a string of real-valued variables are adjusted with the fuzzy controlled COBRA or with DE+PSO. Two classification problems (image and speech recognition problems) were solved with these approaches. Experiments showed that both cooperative optimization techniques demonstrate high performance and reliability in spite of the complexity of the solved optimization problems. The workability and usefulness of the proposed meta-heuristic optimization algorithms are confirmed.