Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment

Zou, Zhihong; Yun, Yi; Sun, Jing-nan

doi:10.1016/s1001-0742(06)60032-6

Cited by 801 publications

(369 citation statements)

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“…On the other hand, if the difference is smaller and the entropy is higher, the relative weight would be smaller. Hence, the entropy theory is an objective way for weight determination (Zou et al, 2006). …”

Section: Entropy Methodsmentioning

confidence: 99%

Untitled

2017

Eur. j. interdiscip. stud.

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Section: Entropy Methodsmentioning

confidence: 99%

Untitled

2017

Eur. j. interdiscip. stud.

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“…In informatics, entropy reveals how much information the data provide [38]. For one indicator, the larger the difference among objectives, the smaller is the entropy, which means it provides more useful information and results for a larger weight.…”

Section: Entropy Weight Methodsmentioning

confidence: 99%

Multi-Layered Capital Subsidy Policy for the PV Industry in China Considering Regional Differences

Chi

Zhang

et al. 2016

Sustainability

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Abstract:As a country with huge energy consumption, China has been paying more and more attention to green growth in recent years. Several subsidy policies have been conducted to boost the photovoltaic (PV) industry so far. However, as a matter of fact, there are 31 provinces and municipalities (PM) in mainland China, and the economic condition, environmental resources and energy structure of each PM are all significantly different, which leads to a discrepancy of PV efficiency among regions. This paper proposes that the subsidies for the PV industry should be considered mainly from three aspects: the PM's economic condition, energy efficiency and environmental responsibility. We built 19 evaluation indicators involving economic, environmental and energy factors, allocated weight to each indicator using the entropy weight method and sorted the 31 evaluation objects by TOPSIS (Technique for Order of Preference by Similarity to the Ideal Solution) method. Additionally, through an empirical study, we obtained the subsidy proportion for each PM. The result could make much of a contribution to the green growth of different regions and to the whole country.

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“…By contrast, information entropy can be a useful measure of the information content of data. If there are great differences in value among the items that compose an indicator, then the information entropy of the indicator is relatively small, i.e., the indicator provides useful information and therefore should be weighted heavily [43]. Accordingly, we adopt the entropy method in this study to determine the weights of the indicator system used to evaluate urban competitiveness.…”

Section: Weighting Methodsmentioning

confidence: 99%

Measuring and Analysis of Urban Competitiveness of Chinese Provincial Capitals in 2010 under the Constraints of Major Function-Oriented Zoning Utilizing Spatial Analysis

Wang

Ren

et al. 2014

Sustainability

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Urban competitiveness aids local development by encouraging the exploitation of opportunities for economic development and by enhancing overall performance. Previous studies have evaluated urban competitiveness primarily from an economic perspective and few studies have considered locational conditions as factors that might influence local industrialization and urbanization. In response to the publishing of a national plan for the development of major function-oriented zones (MFOZs) in 2010, the present essay employs MFOZs as constraints to enable a balanced and comprehensive study of urban competitiveness that includes four dimensions of competitiveness: Economic, social-cultural, environmental, and locational (accessibility and hypsography). A four-level hierarchical indicator system and an entropy weighting method were used to assess the urban competitiveness of 31 Chinese provincial capitals based on a spatial analysis of data acquired in 2010 using Geographic Information System technology. The results reveal the overall ranking of provincial capitals in terms of urban competitiveness and their performances with respect to the four dimensions of competitiveness. Unlike OPEN ACCESSSustainability 2014, 6 3375 previous studies, this analysis was performed by overlaying the strategy of the national MFOZ with the urban competitiveness rankings. The development orientation of each provincial city is discussed according to its characteristics of urban competitiveness under the conditions of a MFOZ.

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Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment

Cited by 801 publications

References 1 publication

Untitled

Untitled

Multi-Layered Capital Subsidy Policy for the PV Industry in China Considering Regional Differences

Measuring and Analysis of Urban Competitiveness of Chinese Provincial Capitals in 2010 under the Constraints of Major Function-Oriented Zoning Utilizing Spatial Analysis

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