粒子群优化
水准点(测量)
多群优化
数学优化
量子
计算机科学
范围(计算机科学)
人口
元启发式
算法
数学
物理
量子力学
社会学
人口学
程序设计语言
地理
大地测量学
作者
Jun Sun,Wenbo Xu,Feng Bin
出处
期刊:IEEE Conference on Cybernetics and Intelligent Systems
日期:2005-07-06
卷期号:1: 111-116
被引量:669
标识
DOI:10.1109/iccis.2004.1460396
摘要
Based on the quantum-behaved particle swarm optimization (QPSO) algorithm, we formulate the philosophy of QPSO and introduce a so-called mainstream thought of the population to evaluate the search scope of a particle and thus propose a novel parameter control method of QPSO. After that, we test the revised QPSO algorithm on several benchmark functions and the experiment results show its superiority.
科研通智能强力驱动
Strongly Powered by AbleSci AI