多目标协同进化算法及其应用研究  

Multi-objective co-evolutionary algorithm and its application

作　　者：李学哲[1] 赵美虹[1] 唐佳佳[1] 

机构地区：[1]苏州科技学院电子与信息工程学院,江苏苏州215009

出　　处：《苏州科技学院学报（自然科学版）》2015年第3期43-46,69,共5页Journal of Suzhou University of Science and Technology （Natural Science Edition）

基　　金：苏州科技学院院科研基金资助项目(Z1325)

摘　　要：协同进化算法(简称CEA:Co-Evolution Algorithm)是通过模拟竞争与协同并存的生物进化机理来求解问题的人工智能技术,它特别适用于维数较高或结构复杂系统的优化问题。文中在多目标协同进化算法研究基础上,设计了基于协同进化的血压峰值并行搜索算法,通过峰值与周期信息的"相互"协同作用,使脉搏波峰值解不断地优化,从而提高了搜索速度和准确性,同时也为血压示波法提出了一种新的峰值检测方法。Co-evolutionary algorithm is used to solve the problem by simulating the competition and collaborative coexistence mechanism of biological evolution of artificial intelligence technology. It is particularly suitable for high dimension or structural optimization of complex systems. On the basis of multi-objective co-evolutionary algorithm,this paper designed a blood pressure peak parallel search algorithm based on co-evolution. Through the synergy between peak and period information,the peak pulse wave continuously optimizes the solution,thereby improving the search speed and accuracy. We also proposed a new method for detecting the peak oscillometric method of blood pressure.

关 键 词：协同进化 适应度 多目标优化 示波法 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]