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基于改进BP神经网络的柘林湾水质综合评价模型

Comprehensive Assessment Model of Seawater Quality in Zhelin Bay Based on Improved BP Neural Network

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【Author】 LIN Xiao-ping1, HUANG Chang-jiang2, DU Hong2, CHEN Xu-ming3 (1. Department of Mathematics, Shantou University, Shantou Guangdong 515063, China)(2. Institute of Aquatic Technology and Environmental Resources Protection, Shantou University, Shantou Guangdong 515063, China)(3. Shantou Oceanic and Fishery Administration, Shantou Guangdong 515041, China)

【机构】汕头大学数学系；汕头大学水生生物技术与环境资源保护研究所；汕头市海洋与渔业局广东汕头515063；广东汕头515063；广东汕头515041；

【摘要】建立了基于改进 BP神经网络的柘林湾水质综合评价模型 .实验结果表明 ,新模型的网络训练收敛速度比未改进的模型快、误差更小 ,而且能克服 BP网络所存在的“过拟合”现象 .因此 ,它的泛化能力强 ,结果客观、合理 .更多还原

【Abstract】 A comprehensive model based on developed BP neural network for assessing seawater quality in Zhelin Bay has been established. The experimental results have shown that the new model converges faster and the error is less than original BP network. Moreover, the new model can avoid being overfitted during the network training, so it possesses the capacity of higher generalization than the original model, and its assessed results are objective and reliable also.更多还原

【关键词】水质综合评价； BP神经网络； LM算法；过拟合；泛化能力；
【Key words】 comprehensive assessment of seawater quality； BP neural network； LM algorithm； overfitting； generalization；

【基金】广东省重大科技兴海项目 (A2 0 0 0 0 5 F0 2 );广东省自然科学基金项目 (0 2 1 2 60 )

【文献出处】数学的实践与认识 ,Mathematics In Practice and Theory , 编辑部邮箱 ,2004年11期

【分类号】X824
【被引频次】8
【下载频次】259

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