مقاله شبیه سازی شده

کد پروژه: 1004

 

موضوع:الگوریتم pso و سیستم آشوب

 

شامل:مقاله اصلی + فایل شبیه سازی با نرم افزار متلبMatlab +گزارش کامل از خلاصه ای از مقاله و نتایج شبیه سازی

 

عنوان مقاله:

Parameter identification of chaotic dynamic systems throughan improved particle swarm optimization

آدرس:sciencedirect



خلاصه:

Abstract

This paper is concerned with the parameter identification problem for chaotic dynamic systems. An improved particle swarm optimization (IPSO), which is a novel evolutionary computation technique, is proposed to solve this problem. The feasibility of this approach is demonstrated through identifying the parameters of Lorenz chaotic system. The performance of the proposed IPSO is compared with the genetic algorithm (GA) and standard particle swarm optimization (SPSO) in terms of parameter accuracy and computational time. It is illustrated in simulations that the proposed IPSO is more successful than the SPSO and GA. IPSO is also improved to detect and determine the variation of parameters. In this case, a sentry particle is introduced to detect any changes in system parameters and if any change is detected, IPSO runs to find new optimal parameters. Hence, the proposed algorithm is a promising particle swarm optimization algorithm for system identification.

Keywords

Collaborative filtering; Recommender systems; Similarity measures; Metrics; Genetic algorithms; Performance

 

سفارش پروژه