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Entropy 2017, 19(11), 574; https://doi.org/10.3390/e19110574

Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles

1
School of Civil Engineering and Environmental Engineering, Anhui Xinhua University, Hefei 230088, China
2
Institute of Safety and Environmental Assessment, Anhui Xinhua University, Hefei 230088, China
3
School of Civil Engineering, Hefei University of Technology, Hefei 230009, China
4
Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Received: 5 September 2017 / Revised: 7 October 2017 / Accepted: 19 October 2017 / Published: 25 October 2017
(This article belongs to the Special Issue Entropy Applications in Environmental and Water Engineering)
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Abstract

As a new development form for evaluating the regional water resources carrying capacity, forewarning regional water resources of their carrying capacities is an important adjustment and control measure for regional water security management. Up to now, most research on this issue have been qualitative analyses, with a lack of quantitative research. For this reason, an index system for forewarning regional water resources of their carrying capacities and grade standards, has been established in Anhui Province, China, in this paper. Subjective weights of forewarning indices can be calculated using a fuzzy analytic hierarchy process, based on an accelerating genetic algorithm, while objective weights of forewarning indices can be calculated by using a projection pursuit method, based on an accelerating genetic algorithm. These two kinds of weights can be combined into combination weights of forewarning indices, by using the minimum relative information entropy principle. Furthermore, a forewarning model of regional water resources carrying capacity, based on entropy combination weight, is put forward. The model can fully integrate subjective and objective information in the process of forewarning. The results show that the calculation results of the model are reasonable and the method has high adaptability. Therefore, this model is worth studying and popularizing. View Full-Text
Keywords: water resource carrying capacity; forewarning model; entropy of information; fuzzy analytic hierarchy process; projection pursuit; accelerating genetic algorithm water resource carrying capacity; forewarning model; entropy of information; fuzzy analytic hierarchy process; projection pursuit; accelerating genetic algorithm
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Zhou, R.; Pan, Z.; Jin, J.; Li, C.; Ning, S. Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles. Entropy 2017, 19, 574.

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