Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles
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 qualitati...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-10-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/19/11/574 |
| _version_ | 1817991861170601984 |
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| author | Rongxing Zhou Zhengwei Pan Juliang Jin Chunhui Li Shaowei Ning |
| author_facet | Rongxing Zhou Zhengwei Pan Juliang Jin Chunhui Li Shaowei Ning |
| author_sort | Rongxing Zhou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T01:18:34Z |
| format | Article |
| id | doaj.art-9dcca135541345ee9d8080b3f7455da0 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-14T01:18:34Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-9dcca135541345ee9d8080b3f7455da02022-12-22T02:20:44ZengMDPI AGEntropy1099-43002017-10-01191157410.3390/e19110574e19110574Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy PrinciplesRongxing Zhou0Zhengwei Pan1Juliang Jin2Chunhui Li3Shaowei Ning4School of Civil Engineering and Environmental Engineering, Anhui Xinhua University, Hefei 230088, ChinaSchool of Civil Engineering and Environmental Engineering, Anhui Xinhua University, Hefei 230088, ChinaSchool of Civil Engineering, Hefei University of Technology, Hefei 230009, ChinaKey Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, ChinaSchool of Civil Engineering, Hefei University of Technology, Hefei 230009, ChinaAs 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.https://www.mdpi.com/1099-4300/19/11/574water resource carrying capacityforewarning modelentropy of informationfuzzy analytic hierarchy processprojection pursuitaccelerating genetic algorithm |
| spellingShingle | Rongxing Zhou Zhengwei Pan Juliang Jin Chunhui Li Shaowei Ning Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles Entropy water resource carrying capacity forewarning model entropy of information fuzzy analytic hierarchy process projection pursuit accelerating genetic algorithm |
| title | Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles |
| title_full | Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles |
| title_fullStr | Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles |
| title_full_unstemmed | Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles |
| title_short | Forewarning Model of Regional Water Resources Carrying Capacity Based on Combination Weights and Entropy Principles |
| title_sort | forewarning model of regional water resources carrying capacity based on combination weights and entropy principles |
| topic | water resource carrying capacity forewarning model entropy of information fuzzy analytic hierarchy process projection pursuit accelerating genetic algorithm |
| url | https://www.mdpi.com/1099-4300/19/11/574 |
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