通过建立珠江口2009年夏季水质综合评价的自组织特征映射网络模型,探索了珠江口不同河段水质状况。结果表明,利用自组织特征映射网络人工神经网络可以直观清晰地对珠江口海域水质空间进行分类。珠江口海域水质可分为三大类,第一类为受到人类活动影响显著的广州河段区域;第二类为内伶仃洋海域,该区域主要受到咸淡水混合的影响;第三类为主要受到外海水交换影响的外伶仃洋海域。结果阐明人工神经网络模型能为珠江口环境保护与生物资源可持续利用提供科学的决策依据。 By establishing the self-organizing feature map network model of comprehensive evaluation of water quality in the summer of 2009 in the Pearl River Estuary, the water quality in different reaches of the Pearl River Estuary was explored. The results show that the water quality space in the Pearl River Estuary can be categorized intuitively and clearly using the self-organizing feature map network artificial neural network. The water quality of the Pearl River Estuary can be divided into three categories, the first is the Guangzhou Reach region which is significantly affected by human activities; the second is the Nei Lingding Sea, which is mainly affected by the mixture of fresh and brackish water; the third category is mainly The outer Lingdingyang sea affected by the sea water exchange. The results show that artificial neural network model can provide scientific decision-making basis for the sustainable utilization of environmental protection and biological resources in the Pearl River Mouth.