摘要
鉴于常规差分进化算法容易“早熟” ,全局寻优能力有待提高 ,提出了基于优进策略的差分进化算法 ,利用种群繁衍的有用信息改进子代分布 ,并引入确定性寻优操作 ,以提高寻优性能 .设计了单纯形寻优操作和重布操作 ,并调整有关概率等 .测试表明新算法的全局寻优性能有明显改善 ,已成功地应用于铯 铷 钒系低温硫酸催化剂上SO2 氧化反应模型参数的估计 。
In this study a modified evolution algorithm(MDE) was proposed to improve the searching efficiency of simple differential evolution algorithm(DE). The modified evolution algorithm improved the performance of global optimization through collecting population information during evolution and at the same time introducing deterministic operation, amending distribution of individuals adaptively. The methods proposed include maintaining population diversity, adding new deterministic simplex searching operation, modifying the probability operation, and others. A typical example indicated good performance of this algorithm. Finally, the MDE has been successfully applied to nonlinear parameter estimation of the model of low temperature SO2 oxidation with Cs-Rb-V sulfuric acid catalyst.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2004年第4期598-602,共5页
CIESC Journal
基金
国家自然科学基金资助项目 (No 2 0 0 760 41)~~
关键词
差分进化
优进策略
化学反应速率
参数估计
建模
Chemical reactions
Evolutionary algorithms
Mathematical models
Parameter estimation
