Assessment and sequencing of air target threat based on intuitionistic fuzzy entropy and dynamic VIKOR

Zhang, Kun; Kong, Weiren; Li, Peipei; Shi, Jiao; Lei, Yu; Zou, Jie

doi:10.21629/jsee.2018.02.11

Cited by 48 publications

(20 citation statements)

References 3 publications

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“…The main advantages of this paper can be given as follows: (1) the TOPSIS method is extended by PLTSs with unknown weight information; (2) the probabilistic linguistic TOPSIS method is proposed to solve the probabilistic linguistic MAGDM problems with entropy weight; (3) a case study for supplier selection of new agricultural machinery products is supplied to show the developed approach; (4) our proposed PL-TOPSIS method emphasis the distance similarity degree from the positive and negative ideal solution with entropy weight; and (5) In this research, the TOPSIS method, which may be also a resultful MADM or MAGDM method, has been designed to tackle uncertain decision-making problems. In the future, the application of the proposed models and methods with PLTSs needs to be investigated into other uncertain decision making [ 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ] and other uncertain and fuzzy environment [ 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 ].…”

Section: Discussionmentioning

confidence: 99%

TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

Wei

et al. 2019

Entropy

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In multiple attribute group decision making (MAGDM) problems, uncertain decision information is well-represented by linguistic term sets (LTSs). These LTSs are easily converted into probabilistic linguistic sets (PLTSs). In this paper, a TOPSIS method is proposed for probabilistic linguistic MAGDM in which the attribute weights are completely unknown, and the decision information is in the form of probabilistic linguistic numbers (PLNs). First, the definition of the scoring function is used to solve the probabilistic linguistic entropy, which is then employed to objectively derive the attribute weights. Second, the optimal alternatives are determined by calculating the shortest distance from the probabilistic linguistic positive ideal solution (PLPIS) and on the other side the farthest distance of the probabilistic linguistic negative ideal solution (PLNIS). This proposed method extends the applications range of the traditional entropy-weighted method. Moreover, it doesn’t need the decision-maker to give the attribute weights in advance. Finally, a numerical example for supplier selection of new agricultural machinery products is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate. The proposed method can contribute to the selection of suitable alternative successfully in other selection problems.

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Section: Discussionmentioning

confidence: 99%

TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

Wei

et al. 2019

Entropy

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“…The objective difference between index data should be considered when determining the index weight, to avoid the influence of subjective preference on the results. EWM is used to calculate the index weight and objectively quantify the importance of the index, which introduces entropy in information theory to evaluate the relative intensity of the index in the sense of competition [25], [26]. When the index values of evaluation objects differ greatly, the entropy value is small, and the information provided by the index is large, so the weight of the index is also large.…”

Section: Calculate Index Weight With Ewmmentioning

confidence: 99%

Energy Efficiency Evaluation and Optimization of Industrial Park Customers Based on PSR Model and Improved Grey-TOPSIS Method

Zhao

2021

IEEE Access

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Energy efficiency evaluation of industrial park customers is carried out to help customers develop optimization strategies and improve the energy efficiency level. The evaluation indexes are proposed based on pressure-state-response (PSR) model and the redundant indexes are selected by combining principal component analysis (PCA) and correlation analysis. Thus the dynamic energy efficiency index system is constructed. The weight of indexes is calculated by the entropy weight method (EWM). An energy efficiency evaluation model based on improved Grey-technique for order preference by similarity to ideal solution (TOPSIS) is proposed, which replaces the Euclidean distance by weighted grey correlation degree and can accurately evaluate customers' energy efficiency level. An energy efficiency optimization model is proposed, which can maximize optimization benefits while improving energy efficiency. The validity of the evaluation and optimization models is verified by the case study of an industrial park.INDEX TERMS Energy efficiency evaluation, industrial park customers, pressure-state-response model, Grey-technique for order preference by similarity to ideal solution, energy efficiency optimization This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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“…In recent years, the intuitionistic fuzzy set (IFS) [14] has been defined as a union of the membership and nonmembership functions and the degree of hesitation. IFSs can describe the fuzziness and uncertainty of target information and have been widely used in target threat assessment [15][16][17][18]. In [15], IFSs are used to construct an intuitionistic fuzzy target information matrix and conduct target threat assessment.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Air Target Threat Assessment Based on Interval-Valued Intuitionistic Fuzzy Sets, Game Theory, and Evidential Reasoning Methodology

Zhao

Yang

et al. 2021

Mathematical Problems in Engineering

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In order to reduce the uncertainty of target threat assessment results and improve exact target assessment in the complicated and changeable air combat environment, a novel method based on the combination of interval-valued intuitionistic fuzzy sets (IVIFSs), game theory, and evidential reasoning methodology is proposed in this paper. First, the imprecise and fuzzy information of battlefield air target is expressed by IVIFS. Second, the optimal index weight is determined by the interval intuitionistic fuzzy entropy and game theory. And the time series weight is calculated by the inverse Poisson distribution method. Then, the target evaluation information at different times is dynamically fused through an evidential reasoning algorithm. Finally, the accuracy function is applied to obtain the threat ranking of all the targets. A case of the threat assessment of air targets is provided to demonstrate the implementation process of the method proposed in this paper. Simulation experiments show that in a rapidly evolving combat environment, this algorithm can effectively reduce the uncertainty of target threat assessment results. It provides us with a useful way for target threat assessment based on interval-valued intuitionistic fuzzy sets, game theory, and evidential reasoning methodology.

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Assessment and sequencing of air target threat based on intuitionistic fuzzy entropy and dynamic VIKOR

Cited by 48 publications

References 3 publications

TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

Energy Efficiency Evaluation and Optimization of Industrial Park Customers Based on PSR Model and Improved Grey-TOPSIS Method

Dynamic Air Target Threat Assessment Based on Interval-Valued Intuitionistic Fuzzy Sets, Game Theory, and Evidential Reasoning Methodology

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