摘要
仿生优化算法是模拟自然中生物体的行为或状态的算法总称。由于该类算法的随机性和相对复杂性,故其应用范围较传统算法更广。介绍了人工神经网络、苍狼算法及鸽群智能算法的背景、基本原理及实现步骤,深入剖析了它们之间的异同,对该类算法的发展远景进行了展望。
Bionic optimization algorithm is a generic term for a class of algorithms that simulates the behavior or state of organisms in nature.Due to the randomness and relative complexity of this type of algorithm,it is wider than traditional algorithms about the applica tion range.This paper proposes the backgrounds,basic principles and implementation steps of three hot or new biology-based algo rithms(artificial neural network,gray wolf algorithm,and pigeon-inspired optimization);then their similarities and differences thor oughly are analyzed;finally,some remarks on the development prospects of the algorithms are presented.
作者
余今
张德贤
YU Jin;ZHANG De-xian(School of Information Science and Engineering,Henan University of Technology,Zhenzhou 450001,China)
出处
《软件导刊》
2019年第2期49-51,共3页
Software Guide
关键词
仿生优化算法
人工神经网络
苍狼算法
鸽群智能算法
bionic optimization algorithm
artificial neural network
grey wolf algorithm
pigeon-inspired optimization