Optimized Parameter of Wavelet Neural Network (WNN) using INGA

Abstract

Genetic algorithm has been one of the most popular methods for many challenging optimization problems. It is a critical problem in which the evacuation time is an important issues. The continuous air traffic growth and limits of resources, there is a need for reducing the congestion of the airspace system. The main objective of this work is to automatically adapt the airspace configurations, according to the evolution of traffic Niche genetic algorithm(INGA) was used in reliability optimization of software system. And also the searching performance of the genetic algorithm was improved by the stochastic tournament model. The multi-module complex software system reliability allocation effectively. Genetic algorithm (GA) and FGA are compared though seven benchmark function. It can be applied to a wider range of problem including multi-level problem. The uniform schema crossover operator and the non-uniform mutation in the genetic algorithm.