Title :
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
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569195
