Forewarning of sustainable utilization of regional water resources: a model based on BP neural network and set pair analysis
Ju-Liang Jin,
Yi-Ming Wei,
Le-Le Zou,
Li Liu,
Wei-wei Zhang and
Yu-liang Zhou
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2012, vol. 62, issue 1, 115-127
Abstract:
Early warning for sustainable utilization of regional water resources is an important control measure for regional water security management. To establish operable and quantitative forewarning model, in this paper, a new forewarning model for sustainable utilization of water resources based on BP neural network and set pair analysis (named BPSPA-FM for short) was established. In the proposed approach, the accelerating genetic algorithm–based fuzzy analytic hierarchy process was suggested to determine the weights of evaluation indexes, back-propagation neural network updating model was used to predict the values of the evaluation indexes, and the set pair analysis was used to determine the function values of relative membership in variable fuzzy set of the samples. BPSPA-FM was applied to early warning for sustainable utilization of regional water resources of Yuanyang Hani terrace in Yunnan Province of China. The results show that the states of sustainable utilization in this system were near the critical value between nonalarm and slight alarm from 1990 to 2000, the states of the system fell into slight alarm and were rapidly close to intermediate alarm from 2001 to 2004, and the states of the system were predicted to be near the critical value between slight alarm and intermediate alarm from 2005 to 2010. The main alarm indexes of the system were utilization ratio of water in agriculture, control ratio of surface water, per capita water supply, per unit area irrigation water and per capita water consumption. BPSPA-FM can take full advantage of the changing information of the evaluation indexes in adjacent periods and the relationship between the samples and the criterion grades. The results of BPSPA-FM are reasonable with high accuracy. BPSPA-FM is general and can be applied to early warning problems of different natural hazards systems such as drought disaster. Copyright Springer Science+Business Media B.V. 2012
Keywords: Water security management; Water resources sustainable utilization; Forewarning model; Fuzzy analytic hierarchy process; Back-propagation neural network; Set pair analysis; Genetic algorithm (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1007/s11069-011-0037-9 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:62:y:2012:i:1:p:115-127
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069
DOI: 10.1007/s11069-011-0037-9
Access Statistics for this article
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk
More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().