scholarly journals Evaluation of Vehicle Handling Stability Based on Interval TOPSIS and Entropy Weights

2021 ◽  
Vol 2095 (1) ◽  
pp. 012055
Author(s):  
Xincheng Huang
Keyword(s):  
Evaluation Criteria ◽  
Topsis Method ◽  
Entropy Weight ◽  
Interval Numbers ◽  
Vehicle Handling ◽  
Relative Closeness ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Interval Weight ◽  
Ranking Index

Abstract The purpose of this study is to evaluate the handling stability of vehicle from the perspective of users using a multi-criteria decision-making approach with interval numbers. In order to achieve this purpose, the evaluation criteria easy for drivers to understand were constructed based on questionnaire, the interval weights of the criteria were calculated using the entropy weight method with interval numbers, and the interval TOPSIS method was used to evaluate the vehicle handling stability. As the improvement of the method, a new method to determine the crisp value of the interval weight was given, and the relative closeness index used for ranking alternatives was extended to a new additive ranking index. The proposed method was used to evaluate the handling stability of 12 vehicles, and the results may provide some basis for vehicle R & D and design.

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 Assessment of the Ecological Niche of Photovoltaic Agriculture in China

2019 ◽  
Vol 11 (8) ◽  
pp. 2268 ◽  
Author(s):  
Wang ◽  
Wang ◽  
Chen
Keyword(s):  
Ecological Niche ◽  
Cloud Model ◽  
Development Trend ◽  
Evaluation Index System ◽  
Entropy Weight ◽  
Interval Numbers ◽  
Good State ◽  
Entropy Weight Method ◽  
Weight Method ◽  
The Development Trend

To evaluate the ecological niche of photovoltaic agriculture in China, an evaluation index system was constructed. Based on the presentation form of interval numbers, we used the interval entropy weight method and interval cloud model to measure the niche state value and niche role value of photovoltaic agriculture. In this way, we determined the development trend of the ecological niche of photovoltaic agriculture. The results show that Chinese photovoltaic agriculture is in a good state and plays a good, but weak, role. The ecological niche of China’s photovoltaic agriculture will undergo a four-stage evolution process: positioning, integration, leap, and symbiosis. China has completed the positioning stage and entered the integration stage. Hence, it is important to constantly improve the level of industrial integration technology and to form a new photovoltaic agriculture recycling economic ecosystem.

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 A Computational Model Based on Shannon Entropy to Analyze Social Development in South America

2019 ◽  
Vol 8 (11) ◽  
pp. 2515-2522
Keyword(s):  
South America ◽  
Social Development ◽  
Evaluation Criteria ◽  
South American ◽  
Entropy Weight ◽  
The Social ◽  
Qualitative Variables ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Using Data

In the world, the level of social development of a country is an important factor since it guarantees the improvement of the quality of life in its population. In this study, we evaluated social development using quantitative and qualitative variables to measure the level of development of South American countries. The entropic-weight method, from Shannon's entropy theory, was applied for the purpose of obtaining a classification showing the social development level in the countries on the list. To calculate the weight of the criteria, the entropy-weight method was applied, followed by the classification of the countries studied in concordance with a weighted sum. In this work, thirteen criteria and ten countries were studied, using data from the year 2016. The results showed that the two best ranked countries were Chile and Uruguay, and the two worst ranked countries were Venezuela and Colombia. In addition, an informative map of social development in the mentioned countries, which varies in a scale of colors, was presented. As a result, the method used in the present article revealed interesting results and it could be used on other social studies considering additional evaluation criteria. The results of this work could serve to governments of South America countries to make the best decision on social problems.

A new cross-efficiency ranking method in group decision making environment

2021 ◽  
pp. 1-13
Author(s):  
Meiqin Wu ◽  
Xiaoqing Hou ◽  
Jianping Fan
Keyword(s):  
Decision Making ◽  
Evaluation Criteria ◽  
Extended Model ◽  
Entropy Weight ◽  
Optimal Weights ◽  
Relative Evaluation ◽  
Entropy Weight Method ◽  
Efficiency Ranking ◽  
Weight Method ◽  
Decision Making Units

As an extended model of data envelopment analysis (DEA), cross-efficiency is utilized in various fields. It applies the relative evaluation values of homogeneous decision-making units (DMUs) in ranking completely. Due to the non-uniqueness of DEA optimal weights, and the cross-efficiency methods focus on the aggregation of cross-efficiency matrix values. There is a low correction between the final efficiency evaluation value and the value assigned to the criteria weight or the value of the criteria. This paper uses the modified aggressive cross-efficiency model to calculate the weights of the decision-making units (DMUs). Then according to the consistency of peer-evaluation criteria, the entropy weight method is used to aggregate the index weights to generate a set of common weights, and a new Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method is used to calculate the utility score of DMUs that can rank them completely. Finally, a numerical case of supplier selection is offered to illustrate the feasibility and effectiveness of the proposed method.

scholarly journals A FUZZY MULTI-ATTRIBUTE DECISION-MAKING METHOD UNDER RISK WITH UNKNOWN ATTRIBUTE WEIGHTS / NERAIŠKUSIS MAŽESNĖS RIZIKOS DAUGIATIKSLIS SPRENDIMŲ PRIĖMIMO METODAS SU NEŽINOMAIS PRISKIRIAMAIS REIKŠMINGUMAIS

2011 ◽  
Vol 17 (2) ◽  
pp. 246-258 ◽  
Author(s):  
Zuosheng Han ◽  
Peide Liu
Keyword(s):  
Decision Making ◽  
Data Types ◽  
Decision Matrix ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Entropy Weight Method ◽  
Multi Attribute Decision Making ◽  
Weight Method ◽  
Multiple Attributes Decision Making

This paper aims at solving hybrid multiple attributes decision-making problems under risk with attribute weight known and a new decision approach based on entropy weight and TOPSIS is proposed. First, the risk decision matrix is transformed into the certain decision matrix based on the expectation value. Then, the deviation entropy weight method is used to determine the attribute weights. And according to the definitions of the distance and the positive/negative ideal solutions for different data types, the relative closeness coefficients can be calculated by TOPSIS. Furthermore, the alternatives are ranked by the relative closeness coefficients. Finally, an application case is given to demonstrate the steps and effectiveness of the proposed approach. Santrauka Šiame straipsnyje siekiama išspręsti mišrias mažesnės rizikos daugiatiksles sprendimo priėmimo problemas su žinomu priskiriamu reikšmingumu bei yra siūlomas naujas sprendimų priėmimo metodas grindžiamas entropijos reikšmingumu ir TOPSIS. Pirmiausia, rizikos sprendimų matrica yra transformuojama į tam tikrą sprendimų matricą, grindžiamą galimybės verte. Tuomet yra naudojamas entropijos reikšmingumo nuokrypio metodas norint nustatyti priskiriamą reikšmingumą. Atsižvelgiant į atstumo apibrėžimus ir teigiamus / neigiamus idealius sprendimus skirtingiems duomenų tipams, santykinio artumo koeficientas gali būti apskaičiuojami remiantis TOPSIS. Be to, alternatyvos yra reitinguojamos pagal santykinio artumo koeficientus. Galiausiai, yra pateiktas pritaikymo atvejis, siekiant parodyti visus žingsnius ir siūlomo metodo veiksmingumą.

scholarly journals An Optimization Route Selection Method of Urban Oversize Cargo Transportation

2021 ◽  
Vol 11 (5) ◽  
pp. 2213
Author(s):  
Da Huang ◽  
Mei Han
Keyword(s):  
Influencing Factors ◽  
Cloud Model ◽  
Route Selection ◽  
Topsis Method ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Cargo Transportation ◽  
Transportation Routes ◽  
Transportation Route

In order to select the optimal transportation route among alternative transportation routes more accurately and objectively, the choice of urban oversize cargo transportation routes was studied by taking the optimization weight–TOPSIS combination method for specific calculations. This model, based on an entropy weight method, cloud model, and TOPSIS method, combines the superiority of the cloud model for reflecting the randomness and discreteness of subjective evaluation with the advantages of the TOPSIS method in dealing with the problem of multi-objective programming. Through selecting and classifying several the main road influencing factors of urban oversize cargo transportation, based on the data of four urban roads, the entropy weight method is used to initially determine the weights of each influencing factor, the cloud model is used to optimize weights, the TOPSIS method is used to compare and evaluate the paths, and the optimal transportation route is selected on this basis. The results showed that the optimization weight–TOPSIS method is scientific and accurate for the multi-objective planning of oversize cargo transportation route selection, and solves the problem of the impact of subjective factors in existing methods and the difficulty of processing multiple influencing factors. The Pearson consistency test results show that the Pearson correlation coefficient between the proposed method and the actual oversize cargo transportation route selection is 0.995, which is higher than the calculation results without using the combination weight.

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