Identification of Dynamic Models by Using Metaheuristic Algorithms

Abstract

A modified versions of metaheuristic algorithms are presented to compare their performance in identifying the structural dynamic systems. Genetic algorithm, biogeography based optimization algorithm, ant colony optimization algorithm and artificial bee colony algorithm are heuristic algorithms that have robustness and ease of implementation with simple structure. Different algorithms were selected some from evolution algorithms and other from swarm algorithms to boost the equilibrium of global searches and local searches, to compare the performance and investigate the applicability of proposed algorithms to system identification; three cases are suggested under different conditions concerning data availability, different noise rate and previous familiarity of parameters. Simulation results show these proposed algorithms produce excellent parameter estimation, even with little measurements and a high noise rate.

Analysis of New Business Opportunities from Online Informal Education Mediamorphosis Through Digital Platforms

“…on the use of internet technology to manage their operations. Undoubtedly, the existence of the Internet also creates an information revolution that must be realized by all audiences [14], [15]. For a read-only letter, loading takes a long time.…”