Assessment model for water shortage based on neural network classificatory of fuzzy sets

Author

Wang, Fuqiang ; Han, Yuping

Author_Institution

Dept. of Water Conservancy, North China Univ. of Water Resources & Hydropower, Zhengzhou, China

Volume

2

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

841

Lastpage

845

Abstract

An assessment method for water shortage risk based on neural network classificatory of fuzzy sets is presented in paper. Risk rate, weakness, possibility of recovery, period for reoccurrence and risk level are defined as the indexes for water shortage risk assessment of regional resources. The suggested model is used to evaluate water shortage risk of Zhanghe irrigation region in Hubei Province in 1995, 2000, 2005, 2010 and 2020. The evaluation results are in line with the situation about the level of water exploitation and utilization. The model expresses people´s knowledge and experience with fuzzy concepts and utilizes the strong learning ability of neural network. It is more operative and practical that this model is applied to evaluate water shortage risk.

Keywords

environmental science computing; fuzzy set theory; learning (artificial intelligence); neural nets; pattern classification; risk management; fuzzy set theory; neural network learning; water shortage risk assessment method; water shortage risk evaluation; Artificial neural networks; Fuzzy sets; Indexes; Risk management; Training; Water conservation; Water resources; Zhanghe irrigation region; fuzzy sets theory; neural network; risk assessment; water shortage;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5931-5

Type

conf

DOI

10.1109/FSKD.2010.5569195

Filename

5569195