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Application of Discrete Hopfield Neural Network to the Assessment of Nutritional Status in Lakes and Reservoirs:A Case Study on 24 Lakes and Reservoirs in China
Author(s): 
Pages: 10-14,34
Year: Issue:  7
Journal: Journal of Yangtze River Scientific Research Institute

Keyword:  富营养化评价人工神经网络Hopfield网络湖库;
Abstract: 基于离散Hopfield神经网络联想记忆特性,建立了湖库富营养化等级综合评价模型,对全国24个湖库进行富营养化等级综合评价,并与文献投影寻踪法、评分指标法和LM - BP网络法的评价结果进行比较.结果表明:①离散Hopfield神经网络运用于湖库营养化等级评价具有简单、直观,容易实现等优点,其评价结果令人满意;②一般离散Hopfield神经网络并非适用于任何富营养化等级评价,当评价对象单项指标(因子)间存在较大差异时,对象将得不到正确的评价.
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