引用本文:乔俊飞,王会东.模糊神经网络的结构自组织算法及应用[J].控制理论与应用,2008,25(4):703~707.[点击复制]
QIAO Jun-fei,WANG Hui-dong.Structure self-organizing algorithm for fuzzy neural networks and its applications[J].Control Theory and Technology,2008,25(4):703~707.[点击复制]
模糊神经网络的结构自组织算法及应用
Structure self-organizing algorithm for fuzzy neural networks and its applications
摘要点击 2114  全文点击 3986  投稿时间：2006-06-11  修订日期：2007-06-26
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DOI编号  10.7641/j.issn.1000-8152.2008.4.021
  2008,25(4):703-707
中文关键词  自组织  模糊神经网络  预测模型  污水处理
英文关键词  self-organizing  fuzzy neural networks  forecast model  wastewater treatment
基金项目  国家自然科学基金资助项目(60304012, 60674066); 北京市优秀人才培养项目(2006D0501500203); 国家863计划项目(2007AA04Z160).
作者单位E-mail
乔俊飞 北京工业大学 人工智能与机器人研究所, 北京 100022 junfeiq@bjut.edu.cn 
王会东 北京工业大学 人工智能与机器人研究所, 北京 100022 huidong.wang@ia.ac.cn 
中文摘要
      提出了一种新的模糊神经网络自组织算法, 该算法能够基于输入输出数据自动进行结构辨识和参数辨识.首先采用一种自组织聚类方法建立起网络的结构和各参数的初值, 然后采用监督学习来优化网络参数. 通过对非线性函数逼近的分析, 证明了该自组织算法的有效性, 并与其他算法作了比较. 最后, 以某污水处理厂的实际运行数据为对象, 应用该模糊神经网络建立了活性污泥系统出水水质预测模型, 仿真结果表明, 该模型能够对污水处理系统出水水质进行较好的预测.
英文摘要
      A new self-organizing algorithm for fuzzy neural networks is proposed, which automates the structure and parameter identification simultaneously based on input-target samples. Firstly, a self-organizing clustering method is used to establish the network structure and the initial values of its parameters. Then a supervised learning is applied to optimize these parameters. An example of nonlinear function approximation is given to demonstrate the effectiveness of the algorithm, where some comparisons are made with other approaches. Finally, based on the data of a wastewater treatment plant, a forecast model of the output-water quality is developed using the established fuzzy neural networks. Simulation results show that the output-water quality can be well predicted by the model.