Neural network model for environmental predication: case study for China

被引：1
|
作者：
Linyan, Sun [1 ]
Ying, Wang [1 ]
机构：
[1] Management Sch of Xian Jiaotong Univ, Xian, China
来源：
Computers and Industrial Engineering | 1996年 / 31卷 / 3-4期
关键词：
Algorithms - Convergence of numerical methods - Environmental protection - Learning systems - Mathematical models - Neural networks - Pollution;
D O I：
10.1016/S0360-8352(96)00286-0
中图分类号：
学科分类号：
摘要：
In this paper, the popular training method Back-propagation (BP) of Neural Networks (NN) is modified by introducing two parameters into the procedure in order to speed learning and improve the convergence. The modified algorithm is named as BPGM and is successfully used in forecasting the future pollution generation and the investment demand for the environment protection in China. Based on the predication of NN model, the future situation of environment of China is analyzed and the investment in environment protection is compared with the average level of the world. Some policies suggestions are proposed.
引用
收藏
页码：879 / 883
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