scholarly journals Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 867 ◽  
Author(s):  
Huafeng Quan ◽  
Shaobo Li ◽  
Hongjing Wei ◽  
Jianjun Hu
Keyword(s):  
Game Theory ◽  
Grey Relational Analysis ◽  
Evaluation System ◽  
Product Evaluation ◽  
Entropy Method ◽  
Kansei Engineering ◽  
Topsis Method ◽  
Decision Matrix ◽  
Relational Analysis ◽  
Grey Relational

With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users.

scholarly journals Using Grey Relational Analysis with Entropy to Predict the International Financial Center of China

2017 ◽  
Vol 5 (1) ◽  
pp. 88-96 ◽  
Author(s):  
Hang Jiang ◽  
Jan-Yan Lin ◽  
Peng Jiang
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Grey Relational Analysis ◽  
Direct Investment ◽  
Entropy Method ◽  
Relational Analysis ◽  
Key Indicators ◽  
Grey Relational ◽  
International Financial Center ◽  
Total Stock

Abstract The establishment of the China Pilot Free Trade Zone (FTZ) has significantly promoted international trade, financial development, and economic growth. Building international financial centers (IFCs) satisfies the demand for FTZs to facilitate financial development, as well as promoting economic growth. Thus, successfully predicting the next IFC in China under the FTZ framework is an important issue. In this study, we applied grey relational analysis combined with entropy method to predict potential IFCs among seven FTZ cities. According to the results, our interesting findings include: 1) the “total stock turnover”, “total value of imports and exports”, and “Foreign Direct Investment (FDI)” are key indicators for determining future IFCs; 2) among seven cities, Shenzhen and Tianjin are highly likely to become the next IFCs, while Shanghai is already an IFC.

scholarly journals A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey

2021 ◽  
Vol 9 (2) ◽  
pp. 81
Author(s):  
Sami Özcan ◽  
Ali Kemal Çelik
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Entropy Method ◽  
Sensitivity Analyses ◽  
Food Sector ◽  
Relational Analysis ◽  
Machine Selection ◽  
Order Preference ◽  
Topsis Technique ◽  
Grey Relational

<div data-canvas-width="540.0693333333334">The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.</div>

scholarly journals The Development and Application of Crop Evaluation System Based on GRA

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Ruihong Wang ◽  
Liguo Zhang ◽  
Lianjie Dong ◽  
Xiuying Lu
Keyword(s):  
Grey Relational Analysis ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Relational Theory ◽  
Grey System Theory ◽  
Network Technology ◽  
Grey System ◽  
Relational Analysis ◽  
Fuji Apple ◽  
Grey Relational

Ever since it was proposed, grey system theory has attracted the attention of scientific researchers and scholars. And it also has been widely used in many fields and solved a large number of practical problems in production, life, and scientific research. With the development and popularization of computer science and network technology, this traditional mathematical model can be applied more simply and efficiently to solve practical problems. Firstly, this paper, to implement steps of grey relational analysis, has made the exclusive analysis and has made the simple introduction to grey relational analysis characteristics. Then, based on grey relational theory and ASP.NET technology, the crop evaluation system is developed. Lastly, by using Excel and the crop evaluation system, the paper carries out a comprehensive evaluation about eight features of Fuji apple, which is from nine different producing areas, respectively. The experiment results show that the crop evaluation system is effective and could greatly improve the work efficiency of the researcher and expand the application scope.

Data Processing in the Application of Grey Relational Analysis Model in Regional Economic Openness of Evaluation System

2014 ◽  
Vol 685 ◽  
pp. 744-748 ◽  
Author(s):  
Liang Liang Yin ◽  
Zhu Hua Han ◽  
Meng Wu
Keyword(s):  
Grey Relational Analysis ◽  
Evaluation System ◽  
Evaluation Model ◽  
Principal Component ◽  
Original Data ◽  
Analysis Model ◽  
Regional Economic ◽  
Relational Analysis ◽  
Index Value ◽  
Grey Relational

In the process of multi index analysis and evaluation, the index value is normalized and standardized through non-dimensional processing of the original data. The index weight is determined according to each index relative principal component contribution through principal component analysis and principal component extraction. Then, a combined evaluation model will be formed through the grey relational analysis, calculation of each index according to grey weighted relative degree. Scientific applicability of the model will be evaluated through regional economic opening degrees.

The Comprehensive Performance Evaluation to LSSC Based on Grey Relational Analysis

2013 ◽  
Vol 785-786 ◽  
pp. 1477-1479
Author(s):  
Qiang Yang ◽  
Yi Zhuang
Keyword(s):  
Supply Chain ◽  
Grey Relational Analysis ◽  
Evaluation System ◽  
Evaluation Model ◽  
Grey Theory ◽  
Relational Analysis ◽  
Service Supply Chain ◽  
Set Up ◽  
Grey Relational ◽  
Full Consideration

Based on the full consideration of the structure and coordination in the service supply chain, an evaluation system focusing on evaluating the logistics service supply chain performance was set up. In this paper we introduce the grey theory into the evaluation system and construct an evaluation model based on grey relational analysis method. The example shows that the grey relational analysis can whiten the unascertained relationship between the evaluation factors effectively, reduce the influence of subjective factors, and improve the accuracy of the evaluation.

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