东湖污染物来源的智能识别方法

Intelligence method for recognizing pollutant sources in Donghu lake

  • 摘要: 为识别东湖污染物来源,建立排污口与主要致污因子之间的对应关系,提出了污染物来源智能识别方法;该方法巧妙耦合了对应分析、模糊C-均值聚类及聚类有效性函数等方法,并用加速遗传算法有效解决了这一复杂问题。使用该方法于东湖污染物来源识别,快速得出了排污口与污染物之间的6类对应关系,为东湖污染综合治理提供了合理的决策依据。该方法在排污口众多、污染物来源复杂的城市水体污染治理中,具有一定的推广应用价值。

     

    Abstract: In order to recognize the pollutant sources and build the correspondence relationships between contaminated sources and important pollutants,a set of intelligent recognizing method based on correspondence factor analysis and fuzzy C-means clustering(short for IRM-CFA&FCM)is developed IRM-CFA&FCM couples skilfully fuzzy C-means clustering,correspon dence factor analysis and clustering validity funct ion discovered by Xie,etc,and is solved by the accelerating genetic algorithm efficiently.The method is used to monitor water quality in Donghu lake,acquiring six kinds of correspondence relationships and puting forward some reasonable and valuable suggestions for decisions making of renovating Donghu's contamination comprehensively.The method is useful for recognizing pollutant sources of other city water bodies.

     

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