水利水电科技进展Issue(2)：14-19,6.DOI:10.3880/j.issn.10067647.2013.02.004
基于极限学习机的长江流域水资源开发利用综合评价
Comprehensive evaluation of water resources development and utilization in Yangtze River Basin based on extreme learning machine
崔东文1
作者信息
- 1. 云南省文山州水务局，云南 文山摇 663000
- 折叠
摘要
Abstract
In order to accurately and objectively evaluate water resources development and utilization in the Yangtze River Basin, a comprehensive evaluation index system and classification standard of water resources were determined using the analytic hierarchy method. Based on the extreme learning machine (ELM) algorithm, a comprehensive evaluation model for water resources development and utilization was built to evaluate the water resources of the Yangtze River Basin using RBF and BP neural network models as comparing evaluation model. Training samples and testing samples were generated using the random interpolation method to train the ELM comprehensive evaluation model. The results show that the evaluation grade of water resources of the Yangtze River Basin is 4 to 8, which coincides with the water resources reality. Compared with RBF and BP neural network models, the ELM comprehensive evaluation model has better evaluation accuracy and generalization ability, and has the advantages of simplicity, high accuracy, and strong generalization ability.关键词
水资源开发利用/极限学习机/RBF神经网络/BP神经网络/长江流域Key words
water resources development and utilization/extreme learning machine/RBF neural network/BP neural network/the Yangtze River Basin分类
建筑与水利引用本文复制引用
崔东文..基于极限学习机的长江流域水资源开发利用综合评价[J].水利水电科技进展,2013,(2):14-19,6.
