摘要
利用混沌的随机性、遍历性和规律性进行优化计算,搜索全局最优,可以避免系统落入局部最优陷阱.本文将具有均匀分布函数的帐篷映射引入到混沌优化算法中,并与共轭梯度法相结合,比Logistic混沌映射确定的算法能更快、更有效地搜索到全局最优解.仿真表明该算法是有效的。
Using randomness, ergodicity and regularity property of chaos to search the global
optimization can escape from local minima. In this paper, tent map is introduced to chaotic
optimization algorithm and combined with conjugate gradient algorithm. This algorithm has faster and
better ability for searching global optimum solution. It was demonstrated to be better through
simulation.
出处
《电机与控制学报》
EI
CSCD
北大核心
2004年第1期67-70,共4页
Electric Machines and Control
