scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this 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.

Fuzzy Comprehensive Evaluation for Pumped Storage Capacity Determination Based on Entropy Weight Method

2014 ◽  
Vol 960-961 ◽  
pp. 1473-1476 ◽  
Author(s):  
Zhan An Zhang ◽  
Xing Guo Cai
Keyword(s):  
Decision Making ◽  
Storage Capacity ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Entropy Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Pumped Storage ◽  
Capacity Determination

To determine the pumped storage capacity is a comprehensive decision-making problem. This paper presents the entropy weight method to decide the weight in fuzzy comprehensive evaluation. Example analysis shows the effectiveness of the proposed methods.

scholarly journals Restoration Methods Selection for Wood Components of Chinese Ancient Architectures Based on TODIM with Single-Valued Neutrosophic Sets

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaolu. Long ◽  
Lizhi. Liu ◽  
Can. Xiao ◽  
Pengfei. Cheng ◽  
Chengxun. Fu
Keyword(s):  
Decision Making ◽  
Entropy Weight ◽  
Neutrosophic Sets ◽  
Wood Component ◽  
Proposed Model ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Weight Method ◽  
Multicriteria Group Decision Making ◽  
Selection Of

The selection of restoration methods for ancient architectures is of great significance for the protection of human cultural heritage. This paper proposes a novel restoration methods selection approach for wood components of Chinese ancient architectures, in which a multicriteria group decision-making (MCGDM) method with decision-making information is in the form of single-valued neutrosophic sets (SNNSs). Firstly, it establishes an index system by comprehensively considering subjective and objective criteria. In addition, the best-worst method (BWM) and the entropy weight method are combined to produce index weights. Furthermore, the TODIM method is utilized by the single-valued neutrosophic sets to prioritize restoration methods. Finally, a specific case of wood component restoration is conducted to demonstrate the practicability of the proposed model. The robustness and effectiveness of the proposed method is verified by sensitivity analysis and comparison analysis.

scholarly journals Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 877 ◽  
Author(s):  
Yi Cui ◽  
Shangming Jiang ◽  
Juliang Jin ◽  
Ping Feng ◽  
Shaowei Ning
Keyword(s):  
Decision Making ◽  
Water Consumption ◽  
Projection Pursuit ◽  
Crop Water ◽  
Irrigation Scheme ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Projection Pursuit Model ◽  
Grey Relation

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

A Decision Making Model for Urban Mass Transit Planning

2012 ◽  
Vol 178-181 ◽  
pp. 1898-1903
Author(s):  
Cheng Bing Li ◽  
Kui Yang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Decision Model ◽  
Group Decision ◽  
Multiple Objectives ◽  
Decision Makers ◽  
Transit Planning ◽  
Entropy Weight ◽  
Decision Making Problem ◽  
Urban Mass Transit

The urban transit network planning is considered as a group decision making problem with multiple objectives and multiple decision makers, due to the its planning characteristics. A new group decision making method is presented to overcome the problem in current group decision making. With the idea of integration and collaboration, the group decision making problem is turned into the group decision making with multiple objectives and decision makers, and the two stage decision model is established. The dynamic index is transformed into static index with the dynamic multi-valued context, and the first stage decision model is established by entropy weight theory. The weight is given by experts with cluster analysis, and the aggregation model of group decision making is established with relative entropy, in the second stage.

scholarly journals Effectiveness of Entropy Weight Method in Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Yuxin Zhu ◽  
Dazuo Tian ◽  
Feng Yan
Keyword(s):  
Decision Making ◽  
Water Source ◽  
Entropy Weight ◽  
Weighting Method ◽  
Numerical Discrimination ◽  
Differentiation Degree ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Degree Of Differentiation ◽  
Index Weight

Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

scholarly journals Multi-attribute decision-making method based on Taylor expansion

2019 ◽  
Vol 15 (3) ◽  
pp. 155014771983607
Author(s):  
Peng Sun ◽  
Jiawei Yang ◽  
Yongfeng Zhi
Keyword(s):  
Decision Making ◽  
Taylor Expansion ◽  
Weight Vector ◽  
Decision Time ◽  
Decision Makers ◽  
Attribute Weights ◽  
The Matrix ◽  
Multi Attribute Decision Making ◽  
Natural Base ◽  
Reasonable Use

Determining attribute weights is an indispensable step in multi-attribute decision-making problems, and it is also a top priority in the study of multi-attribute decision-making problems. Existing methods for determining attribute weights do not completely and effectively reflect the decision-maker’s dependency preferences, which will result in unreasonable ranking results for decision-makers. To solve this problem, this article proposes a feature-weighted multi-attribute decision-making method based on Taylor expansion. The method uses the natural base and the eigenvalues of the matrix to construct the feature-weighted coefficients and weights; normalizes all the feature vectors of the matrix; and constructs a new weight vector. Combined with the example to analyze and verify, the method makes reasonable use of all decision information, which saves the decision time of decision-makers.

scholarly journals New Uncertainty Measure of Rough Fuzzy Sets and Entropy Weight Method for Fuzzy-Target Decision-Making Tables

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Huani Qin ◽  
Darong Luo
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Theoretical Studies ◽  
Uncertainty Measure ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Rough Fuzzy Set ◽  
Fuzzy Target

In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification. Both of them are effective, but they are not accurate enough. In this paper, we propose a new rough entropy of a rough fuzzy set combining the rough degree with the rough entropy of a knowledge. Theoretical studies and examples show that the new rough entropy of a rough fuzzy set is suitable. As an application, we introduce it into a fuzzy-target decision-making table and establish a new method for evaluating the entropy weight of attributes.

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