投影寻踪模型的改进及其在城市水资源承载能力预测中的应用

在城市水资源承载能力研究中,偏最小二乘回归方法能有效地处理自变量间多重线性相关性问题,但不能较好地处理因变量与自变量间复杂的非线性问题.投影寻踪神经网络耦合模型是处理非线性问题的有力工具,而且神经网络投影寻踪耦合模型稳健性高,但不能较好地处理自变量间多重线性相关性问题.本文把这两种方法结合在一起,建立了基于偏最小二乘回归的神经网络投影寻踪耦合模型,对城市水资源承载能力进行了预测,并取得了满意效果.

Improvement of Projection Pursuit Model and Its Application in Predicting the City Water Resources Capacity

In the study of the city water resources capacity,the method of partial least-squares regression can effectively deal with the problems of multicollinearity among independent variables,but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables.The method of coupling model with neural network and projection pursuit is an ideal tool to deal with the problem of nonlinearity,and it is very steady,but can not ideally solve the problems of multicollinearity among independent variables.The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression to predict the city water resources capacity,the model was found to be able to give satisfactory effect.