改进的AEA算法及其在重油热解模型参数估计中的应用  

Improved AEA and its application on parameter estimation of heavy oil thermal cracking three lumps model

作　　者：梅真贞[1] 李绍军[1] 桑志祥[1] 

机构地区：[1]华东理工大学自动化系,上海200237

出　　处：《计算机与应用化学》2012年第1期71-74,共4页Computers and Applied Chemistry

基　　金：国家自然科学基金资助项目(20976048;21176072)

摘　　要：本文提出了一种结合文化算法的.AEA算法,它利用文化算法中的信度空间来保存种群中的优质个体,然后通过影响函数来生成新种群。改进的AEA算法能够快速收敛到全局最优值,对典型函数的测试和工业模型参数估计的应用表明:改进的算法全局搜索能力和收敛速度比原始的AEA算法有所提高。In the paper,we proposed an AEA combined with cultural algorithm. It uses reliability space of cultural algorithm to save the elite particles of the swarm, and then generate the new population through the influence function.The improved AEA can quickly converge to the global optimal of the typical functions. The results of testing example functions and modeling industry based on neural network show that the global search ability and the convergence rate of the modified algorithm are improved.

关 键 词：AEA算法 文化算法 优化 参数估计 

分 类 号：TQ015.9[化学工程] TP391.9[自动化与计算机技术—计算机应用技术]