Izvorni znanstveni članak
https://doi.org/10.31534/engmod.2018.4.si.05s
An Improved Artificial Fish Swarm Algorithm
Jianshen Peng
; Colleges of Physics and Mechanical & Electronic Engineering, Hechi University, Yizhou, CHINA; Colleges and Universities Key Laboratory of Intelligent Integrated Automation, Guilin University of Electronic Technology, Guilin, CHINA
Zhenwu Wan
; Department of Information Engineering, Huaxia College, Wuhan University of Technology, Wuhan, CHINA
Qingjin Wei
; Colleges of Physics and Mechanical & Electronic Engineering, Hechi University, Yizhou, CHINA
Hui Jiang
; Colleges and Universities Key Laboratory of Intelligent Integrated Automation, Guilin University of Electronic Technology, Guilin, CHINA
Shixiong Wei
; Colleges of Physics and Mechanical & Electronic Engineering, Hechi University, Yizhou, CHINA
Sažetak
The purpose of this paper is to improve the performance of the original AFSA algorithm at the optimal accuracy rate and overcome the weakness of the algorithm which is also trapped in the local optimum. To this end, the original AFSA was further improved based on the tabu strategy. Specifically, the reproduction and death were introduced to protect the best individuals and eliminate poor quality fish, so as to increase convergence and accuracy. Through simulation, it is proved that our solution can achieve high accuracy, good global convergence, and strong resistance to local minimum. The findings bring new light on the application of AFSA and provide valuable reference to studies in related fields.
Ključne riječi
AFSA; tabu strategy; free domain; reproduction and death; swarm intelligence.
Hrčak ID:
218253
URI
Datum izdavanja:
27.3.2019.
Posjeta: 1.945 *