摘要
通过构建BP人工神经网络模型,进行训练识别,应用于评价水源地水质。结果表明:基于BP人工神经网络的农村饮用水水源地水质评价能够改善其他水源地水质评价方法带来的不足,较好地改善评价对全局性的寻优能力,做到合理全面地评价水源地水质。同时,模型反映出了水源地水质变化的复杂性和可模拟性,提高了对水源地水质评价的可靠性和有效性。
A BP neural network model was established and trained to be applied in the evaluation of water quality in water source areas.The results indicate that the evaluation of water quality in water source areas for rural drinking water based on the BP neural network can avoid the disadvantages of other evaluation methods and improve the global optimization ability of the evaluation,and it can be adopted to rationally and fully evaluate the water quality in water sources areas.Meanwhile the model reflects the nonlinear characteristics of water quality in water source areas and improves the reliability and effectiveness of evaluation of water quality in water source areas.
出处
《水利经济》
2011年第5期65-67,74,共3页
Journal of Economics of Water Resources
基金
山东省教育厅重点项目(J06N05)
泰安市大学生科技新行动计划(2010D1010)
关键词
农村饮用水
水源地
水质评价
BP神经网络
rural drinking water
water source area
water quality evaluation
BP neural network
作者简介
伊璇（1989-），山东泰安人，本科生，从事水文与水资源的研究。
通讯作者：庞清江（1957-），男，山东郓城人，博士，从事水资源与水利工程等研究。E-mail：pangqj01@163．com
