中北大学学报（自然科学版）2017，Vol.38Issue(4)：397-403,7.DOI:10.3969/j.issn.1673-3193.2017.04.001
一类改进的人工蜂群算法
A Kind of Improved Artificial Bee Colony Algorithm
摘要
Abstract
Artificial bee colony algorithm presented by Karaboga in 2005 is researched, which imitates the foraging behavior of honeybees.An inertia weight in particle swarm optimization is introduced into artificial bee colony algorithm, and an improved artificial bee colony algorithm with inertia weight(ABCIW) is proposed.Apply ABCIW algorithm to solve the minimum problems of benchmark functions and further to optimize the parameters of BP neural network for predicting the onset number of hand-foot-mouth disease in China.By comparison with basic artificial bee colony algorithm, quick artificial bee colony algorithm and artificial bee colony algorithm with memory, ABCIW algorithm is more suitable for solving the optimization problems of functions.The prediction results of the onset number of hand-foot-mouth disease in China show that ABCIW algorithm has good prediction results and higher stability.关键词
人工蜂群算法/基准函数/手足口病/预测Key words
artificial bee colony algorithm/benchmark function/hand-foot-mouth disease/prediction分类
信息技术与安全科学引用本文复制引用
胡红萍,崔霞霞,续婷,白艳萍..一类改进的人工蜂群算法[J].中北大学学报（自然科学版）,2017,38(4):397-403,7.基金项目
国家自然科学基金资助项目(61275120) （61275120）
