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

Authors

Yu-qin Gao, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, China
Guo-hua Fang
You-peng Xu
Xin Zhang
Li-jun Qu

Author Country (or Countries)

China

Abstract

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.

Suggested Reviewers

N/A

Recommended Citation

Gao, Yu-qin; Fang, Guo-hua; Xu, You-peng; Zhang, Xin; and Qu, Li-jun (2013) "Evaluation of Water Conservancy Project Management Modernization Based on Improved intelligent algorithm," Applied Mathematics & Information Sciences: Vol. 07: Iss. 3, Article 40.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol07/iss3/40