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现代化工  2018, Vol. 38 Issue (8): 213-216    DOI: 10.16606/j.cnki.issn0253-4320.2018.08.047
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神经网络及遗传算法在催化剂设计中的应用
韩晓霞, 赵超凡
太原理工大学电气与动力工程学院, 山西 太原 030024
Application of artificial neural network and genetic algorithm in catalyst design
HAN Xiao-xia, ZHAO Chao-fan
College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
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摘要 结合神经网络、遗传算法及带精英策略的非支配排序遗传算法(NSGA-Ⅱ)的基本原理和特点,综述了其在催化剂设计中的应用步骤和应用实例,对快速高效开发新催化剂有借鉴作用。
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韩晓霞
赵超凡
关键词:  催化剂设计  神经网络  遗传算法  NSGA-Ⅱ    
Abstract: In view of the fundamental principles and characteristics of artificial neural network,genetic algorithm,non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) attached with elite strategy,their application methods and practical examples in designing and optimizing catalysts are reviewed,which can give references for developing novel catalyst fast and efficiently.
Key words:  catalyst design    neural network    genetic algorithm    NSGA-Ⅱ
收稿日期:  2018-01-02      修回日期:  2018-06-05           出版日期:  2018-08-20
TQ015.9  
  TP391.9  
基金资助: 国家自然科学基金项目(21606159)
通讯作者:  韩晓霞(1976-),女,博士,副教授,研究方向为复杂系统建模与优化,通讯联系人,hanxiaoxia@tyut.edu.cn。    E-mail:  hanxiaoxia@tyut.edu.cn
引用本文:    
韩晓霞, 赵超凡. 神经网络及遗传算法在催化剂设计中的应用[J]. 现代化工, 2018, 38(8): 213-216.
HAN Xiao-xia, ZHAO Chao-fan. Application of artificial neural network and genetic algorithm in catalyst design. Modern Chemical Industry, 2018, 38(8): 213-216.
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http://www.xdhg.com.cn/CN/10.16606/j.cnki.issn0253-4320.2018.08.047  或          http://www.xdhg.com.cn/CN/Y2018/V38/I8/213
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