摘要
近年来,我国水资源利用效率有一定提升,但是相比发达国家仍有很大提升空间。借助前人建立的水资源效率评价指标体系,结合BP神经网络学习和存储信息、总结规律并识别事物和智能运算的能力,提出一种基于BP神经网络的水资源利用效率评价方法。应用该方法对锦州、营口、阜新、辽阳4市评价打分,结果表明,该方法拟合效果很好,平均相对误差为1.13%,与专家评分结果相拟合,R2可达0.9963。该方法能够模拟专家的评分偏好及特点,统一标准客观地对水资源利用效率进行综合评价,将主客观结合起来,提高评价结论的可靠性,为区域水资源利用效率评价提供一种新的途径。
In recent years, China has improved its efficiency of water resources utilization, but compared to the developed countries there is still much room. This paper establishes efficiency evaluation index system of water resources through our predecessors, com- bining BP neural networks to acquire and store information, summarize laws and identify capacity and intelligence operations, and present a new method of BP neural networks in evaluation o{ water resources utilization efficiency. By applying the method of Jinzhou, Yingkou, Fuxin, Liaoyang City evaluation scoring, results show that the method works well, the average relative error of 1.22N, that is consistent with expert grading results. R~ is up to 0. 9963. The method of simulating expert rating preferences and characteristics, uniform standard obiective for comprehensive evaluation of water resources utilization efficiency, a combination of subjective and objective, the reliability of evaluation findings is ciency provides a new way. improved for the evaluation of regional water resources utilization effi
出处
《中国农村水利水电》
北大核心
2013年第5期30-32,共3页
China Rural Water and Hydropower
关键词
BP神经网络
水资源利用效率
综合评价
neural network evoiution of water use efficiency comprehensive evaluation
