基于多元线性回归和Bp神经网络的水资源承载力预测研究
study on trend of carrying capacity change for water resource in jinan based on the regressive equation And ANN
水资源承载力的预测对于地区经济发展具有重要意义，利用主成分分析的方法对济南市水资源承载力变化的驱动力进行分析，人口和GDP是影响水资源承载力变化的最主要的驱动因素，通过水资源承载变化驱动因子的多元线性回归模型和人工神经网络模型，分别预测出2010年和2020年年济南市水资源的需求状况，探讨线性和非线性相结合的方法用于水资源预测。
In order to forecast the carrying capacity change for water resources which is of great importance to the local economy, the driving forces of water resources in Jinan is analyzed by using the main factor analysis , and population and GDP are found as the main driving force. Therefore, the regressive equation and ANN model are used respectively to forecast the require and supply of water resources in Jinan. This paper discuss how the linear and non-linear method are used in the forecast of water resource.
郑新奇 、姚慧
水利经济环境科学理论环境科学技术现状
多元线性回归、Bp神经网络、水资源承载力
regressive equation ANN model carrying capacity of water resource
郑新奇 ,姚慧.基于多元线性回归和Bp神经网络的水资源承载力预测研究[EB/OL].(2005-08-24)[2025-08-10].http://www.paper.edu.cn/releasepaper/content/200508-158.点此复制
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