Evaluation of optical camouflage effect based on entropy weight TOPSIS method

2021 ◽  
Author(s):  
Keliang Wang ◽  
Zhigang Liu ◽  
Yiting Wang ◽  
Shengjie Luo
Keyword(s):  
Topsis Method ◽  
Entropy Weight

scholarly journals Identification and Quantification of Node Criticality through EWM–TOPSIS: A Study of Hong Kong’s MTR System

2021 ◽  
Author(s):  
Yifan Zhang ◽  
S. Thomas Ng
Keyword(s):  
Hong Kong ◽  
Public Transportation ◽  
Early Stage ◽  
Network Robustness ◽  
Global Network ◽  
Practical Significance ◽  
Topsis Method ◽  
Urban Resilience ◽  
Network Efficiency ◽  
Entropy Weight

AbstractPublic transport networks (PTNs) are critical in populated and rapidly densifying cities such as Hong Kong, Beijing, Shanghai, Mumbai, and Tokyo. Public transportation plays an indispensable role in urban resilience with an integrated, complex, and dynamically changeable network structure. Consequently, identifying and quantifying node criticality in complex PTNs is of great practical significance to improve network robustness from damage. Despite the proposition of various node criticality criteria to address this problem, few succeeded in more comprehensive aspects. Therefore, this paper presents an efficient and thorough ranking method, that is, entropy weight method (EWM)–technology for order preference by similarity to an ideal solution (TOPSIS), named EWM–TOPSIS, to evaluate node criticality by taking into account various node features in complex networks. Then we demonstrate it on the Mass Transit Railway (MTR) in Hong Kong by removing and recovering the top k critical nodes in descending order to compare the effectiveness of degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), and the proposed EWM–TOPSIS method. Four evaluation indicators, that is, the frequency of nodes with the same ranking (F), the global network efficiency (E), the size of the largest connected component (LCC), and the average path length (APL), are computed to compare the performance of the four methods and measure network robustness under different designed attack and recovery strategies. The results demonstrate that the EWM–TOPSIS method has more obvious advantages than the others, especially in the early stage.

scholarly journals Sustainable Performance Evaluation: Evidence from Listed Chinese Mining Corporations

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 349
Author(s):  
Yuan Ma ◽  
Jingzhi Men ◽  
Mingyu Li ◽  
Xiaoyan Li
Keyword(s):  
Sustainable Development ◽  
Evaluation System ◽  
Industrial Development ◽  
Ideal Solution ◽  
Topsis Method ◽  
Entropy Weight ◽  
Four Dimensions ◽  
Sustainable Performance ◽  
Research Gap ◽  
Development Evaluation

Rapid industrial development has caused a series of environmental problems, which is not conducive to sustainable development of society as a whole. It is necessary to build a sustainable development evaluation system. Most of the existing literature has evaluated corporate sustainable performance from the economy, environment and society on the basis of triple bottom lines. Considering the research gap and the practice need, an evaluation system is established from four dimensions, referred to as economy, society, environment and responsibility management, and 29 indicators are designed to measure these four dimensions. Twenty seven listed Chinese mining corporations are selected as research samples, and the entropy-weight-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is applied to calculate indicators’ weights. Results show that the four dimensions of sustainable performance weights from high to low are society, environment, economy, and management process.

Application of Combination Evaluation for Academic Title Evaluation

2011 ◽  
Vol 50-51 ◽  
pp. 756-760
Author(s):  
Bao Feng Li ◽  
Jing Guo Qu ◽  
Pu Yu Hao
Keyword(s):  
Associate Professor ◽  
Topsis Method ◽  
Entropy Weight ◽  
Base Points ◽  
Subjective Weight ◽  
Evaluation Models ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Double Base

In this paper, using the relevant data of 34 teaching staffs who participate in the academic title evaluation of associate professor in 2010, firstly it introduces the entropy weight method, Topsis method with subjective weight, Topsis method with objective weight and double base points method with subjective weight to evaluate and sort the performance of 34 teaching staffs. Secondly, two combination evaluation models are constructed to do the same work and the conclusions are more science and rational.

scholarly journals Application of TOPSIS Method Based on Entropy Weight -Delphi in the Evaluation of Teachers’ “double-qualified” Ability

2020 ◽  
Vol 165 ◽  
pp. 06050
Author(s):  
Weixia Wang ◽  
He Jun
Keyword(s):  
Evaluation System ◽  
Evaluation Model ◽  
Topsis Method ◽  
Entropy Weight ◽  
Chinese Library Classification ◽  
Evaluation Indexes ◽  
Energy Evaluation ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Index Weight

In order to improve the rationality and fairness of Teachers’ “Double-qualified” Ability, the article establishes an evaluation model based on 14 evaluation indexes of teachers’ “double-qualified” ability. it adopts Delphi - entropy weight method to weight the evaluation index, and then combines TOPSIS method to evaluate the evaluation object. In the evaluation of TOPSIS method, the traditional TOPSIS weight method was improved, and the entropy weight-delphi method was used to determine the index weight, which was a combination of subjective and objective, making the evaluation system more objective, scientific and reasonable.It not only avoids the subjectivity of decision makers and limitations, but also eliminates the phenomenon of indexes in common impact assessment results and finally applies it to a university teacher “Double division and triple energy” evaluation system, to provide theoretical basis and feasibility analysis for the “double type” teachers team construction. Chinese library classification number: O224 Document identification code: A

scholarly journals Application of TOPSIS in the Diagnosis of Vector Borne Diseases

2019 ◽  
Vol 8 (6) ◽  
pp. 5217-5223
Keyword(s):  
Current Model ◽  
Intuitionistic Fuzzy Set ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Entropy Weight ◽  
Vector Borne Diseases ◽  
Intuitionistic Fuzzy ◽  
Vector Borne ◽  
Specific Symptoms ◽  
Intuitionistic Fuzzy Topsis

“Intuitionistic Fuzzy Set” (IFS) is used to manage nebulousness and indecision. In current investigation, another intuitionistic fuzzy TOPSIS method is proposed for decision making by utilizing entropy weight. Current model permits estimating the degree of membership and non-membership of various alternatives assessed over a criterion set. A case study has been carried out to diagnosis of vector borne disease. Criteria’s have been selected according to relevant disease and weight has been assigned to them by medical expert’s committee. It has been established that TOPSIS method can diagnose the VBD diseases using specific symptoms as criteria and VBDs as alternatives. The suggested methodology can help in correct and timely diagnosis of VBDs and provides doctors an innovative diagnostic tool (WHO, 2004; WHO, 2014). The result is validated by applying fuzzy VIKOR method.

scholarly journals A Hybrid Multi-Criteria Decision-Making Approach Based on ANP-Entropy TOPSIS for Building Materials Supplier Selection

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1597
Author(s):  
Chun-Ho Chen
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Building Materials ◽  
Evaluation Criteria ◽  
Analytic Network Process ◽  
Topsis Method ◽  
Entropy Weight ◽  
Suitable Alternative ◽  
Multi Criteria Evaluation ◽  
Network Process

This article will tell you how to combine “entropy” in the model to reduce the bias of multi-criteria evaluation. Subjective weights are usually determined by decision makers based on their professional background, experience and knowledge, and other factors. The objective weight is obtained by constructing an evaluation matrix of the information based on the actual information of the evaluation criteria of the scheme, and obtained through multi-step calculations. Different decision-making methods are based on different weight types. Considering only one of the two weights often leads to biased results. In addition, in order to establish an effective supply chain, buyers must find suitable merchants among suppliers that provide quality products and/or services. Based on the above factors, it is difficult to choose a suitable alternative. The main contribution of this paper is to combine analytic network process (ANP), entropy weight and the technique for order preference by similarity to an ideal solution (TOPSIS) to construct a suitable multi-criteria decision (MCDM) model. By means of ANP-entropy weights to extend the TOPSIS method, ANP-entropy weights are used to replace subjective weights. A supplier selection decision-making model based on ANP-entropy TOPSIS is proposed. At last, the sensitivity analysis shows that, taking the selection of building materials suppliers as an example, the hybrid ANP-entropy TOPSIS method can effectively select suitable suppliers.

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