多元线性回归和Bp神经网络预测水资源承载力──以济南市为例

Trend of Carrying Capacity Changing for Water Resource in Jinan Based on Regressive Equation and ANN──Taking Jinan as An Example

水资源承载力的预测对发展地区经济具有重要意义,利用主成分分析方法对济南市水资源承载力变化的驱动力进行了分析,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年济南市水资源的需求状况,并探讨了将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 was of great importance to the local economy, the driving forces of water resources in Jinan was analyzed by using the main factor analysis , and population and GDP were found as the main driving force. Therefore, the regressive equation and ANN model were used respectively to forecast the require and supply of water resources in Jinan. This paper discussed how the linear and non - linear method were used in the forecast of water resource.