化工学报 ›› 2012, Vol. 63 ›› Issue (9): 2920-2925.DOI: 10.3969/j.issn.0438-1157.2012.09.039

• 过程系统工程 • 上一篇    下一篇

基于数据特征提取的AANN-ELM研究及化工应用

彭荻, 贺彦林, 徐圆, 朱群雄   

  1. 北京化工大学信息科学与技术学院, 北京 100029
  • 收稿日期:2012-06-14 修回日期:2012-06-21 出版日期:2012-09-05 发布日期:2012-09-05
  • 通讯作者: 朱群雄
  • 作者简介:彭荻(1988-),男,博士研究生。
  • 基金资助:

    国家自然科学基金项目(61104131,61074153)。

Research and chemical application of data feature extraction based AANN-ELM neural network

PENG Di, HE Yanlin, XU Yuan, ZHU Qunxiong   

  1. College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2012-06-14 Revised:2012-06-21 Online:2012-09-05 Published:2012-09-05
  • Supported by:

    supported by the National Natural Science Foundation of China(61104131,61074153).

摘要: 针对极限学习机不能有效解决化工过程中高维数据建模的问题,本文将其与自联想神经网络结合,通过自联想神经网络过滤输入数据中存在的冗余信息、提取特征分量,并对所提取的特征分量采用极限学习机进行训练,由此形成了一种基于数据特征提取的AANN-ELM(auto-associative neural network-extreme learning machine)神经网络。同时,以UCI标准数据集进行测试,以精对苯二甲酸(PTA)溶剂系统进行验证,结果表明,AANN-ELM在处理高维数据时具有学习速度快、网络稳定性强、建模精度高的特点,为神经网络在复杂化工生产中的应用提供了新思路。

关键词: 极限学习机, 自联想神经网络, 高维数据, 过程建模

Abstract: The extreme learning machine usually exist the problems on high-dimensional data modeling in chemical process.Aiming at solving these problems,the auto-associative neural network is combined,in which the auto-associative neural network is constructed to filter redundant information and extract characteristic components,and these characteristic components are trained by extreme learning machine.Thus,a data feature extraction based auto-associative neural network-extreme learning machine(AANN-ELM)is formed.Meanwhile,the effectiveness of this network is verified by the UCI standard data sets and the purified terephthalic acid(PTA)solvent system.The result indicates that AANN-ELM has the characteristics of fast learning speed,stable network output,and high model precision in handling with high-dimensional data,which will provide a new way to apply the neural network in complex chemical production.

Key words: extreme learning machine, auto-associative neural network, high-dimensional data, process modeling

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