Evaluation of Water Conservancy Project Management Modernization Based on Improved intelligent algorithm

被引：4

作者：

Gao, Yu-qin ^{[1
,2
]}

Fang, Guo-hua ^{[2
]}

Xu, You-peng ^{[1
]}

Zhang, Xin ^{[2
]}

Qu, Li-jun ^{[2
]}

机构：

[1] Nanjing Univ, Sch Geog & Oceanog Sci, Nanjing 210008, Jiangsu, Peoples R China

[2] Hohai Univ, Coll Water Conservancy & Hydropower, Nanjing, Jiangsu, Peoples R China

来源：

APPLIED MATHEMATICS & INFORMATION SCIENCES | 2013年 / 7卷 / 03期

关键词：

modernization of water conservancy project management; genetic algorithm; improved BP Neural Network; GA-BP;

D O I：

10.12785/amis/070340

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

An improved GA-BP Neural Network model for the evaluation of water conservancy project management modernization is established in this paper. It optimizes the initial weights and threshold of the improved BP neural network with the application of genetic algorithm. Depart from the ability of fast learning and global search, it can also effectively prevent BP neural network from getting into local minimum and obtaining unstable training results. An illustrative example, just as Taizhou Citation River, is analyzed to substantiate the reliability and rationality of the model with its actual water conservancy project management modernization data. Compared with other models, this model shows its superiority.

引用

页码：1173 / 1179

页数：7