Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications

2021 ◽  
Author(s):  
Chenyang Song ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Regression Analysis ◽  
Uncertain Reasoning ◽  
Fuzzy Environment

Analisa Pengaruh Motivasi Konsumen, Persepsi Kualitas, Dan Sikap Konsumen Terhadap Keputusan Pembelian Sepeda Motor PT. Yamaha Indonesia MFG

CICES ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 188-203
Author(s):  
Ria Wulandari ◽  
M. Ifran Sanni ◽  
Dani Ramadhan
Keyword(s):  
Decision Making ◽  
Regression Analysis ◽  
Qualitative Analysis ◽  
Purchase Decisions ◽  
Analysis Method ◽  
Purchasing Decisions ◽  
Processing Data ◽  
Customer Purchases ◽  
Customer Attitudes ◽  
Quantitative And Qualitative Methods

This research is motivated by a decline in motorcycle sales produced by PT. Yamaha Indonesia MFG in the 2014-2018 period. In this research there was a decrease in the decision on the power of interest in customer purchases on PT. Yamaha Indonesia MFG so that later can be analyzed in the formulation of this paper, that how customer take motorcycle purchase decisions amid the phenomenon of competition and increasingly crowded sales rivalries. The purpose of this research was to analyze the influence of motivation, perceived quality, and customer attitudes toward decisions in purchasing Yamaha motorbikes. This research uses quantitative and qualitative methods. The respondents in this research were 100 people who could meet one to five criteria consisting of; initiator (initiator), influencer (influencer), decision making (decider), purchase (buyer), user (user) motorcycle production PT. Yamaha Indonesia MFG. There are 3 hypotheses formulated and tested using the Regression Analysis method. In qualitative analysis it is obtained from the interpretation of processing data by providing information and explanation. In the results of this research shows the results of Motivation, Quality Perception, and Customer Attitudes have a relationship that has a significant impact on Purchasing Decisions.

A two-sided matching decision-making approach based on regret theory under intuitionistic fuzzy environment

2021 ◽  
pp. 1-18
Author(s):  
Xiang Jia ◽  
Xinfan Wang ◽  
Yuanfang Zhu ◽  
Lang Zhou ◽  
Huan Zhou
Keyword(s):  
Decision Making ◽  
Hamming Distance ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Sets ◽  
Regret Theory ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Objective Model ◽  
Single Objective

This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach.

Extended TOPSIS method based on the entropy measure and probabilistic hesitant fuzzy information and their application in decision support system

2021 ◽  
pp. 1-12
Author(s):  
Muhammad Naeem ◽  
Muhammad Ali Khan ◽  
Saleem Abdullah ◽  
Muhammad Qiyas ◽  
Saifullah Khan
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Group Decision ◽  
Hesitant Fuzzy Set ◽  
Entropy Measure ◽  
Fuzzy Information ◽  
Score Functions ◽  
Fuzzy Environment ◽  
Basic Operating

Probabilistic hesitant fuzzy Set (PHFs) is the most powerful and comprehensive idea to support more complexity than developed fuzzy set (FS) frameworks. In this paper, it can explain a novel, improved TOPSIS-based method for multi-criteria group decision-making (MCGDM) problem through the Probabilistic hesitant fuzzy environment, in which the weights of both experts and criteria are completely unknown. Firstly, we discuss the concept of PHFs, score functions and the basic operating laws of PHFs. In fact, to compute the unknown weight information, the generalized distance measure for PHFs was defined based on the Probabilistic hesitant fuzzy entropy measure. Second, MCGDM will be presented with the PHF information-based decision-making process.

DECISION MAKING BY VARIABLE CONTRIBUTION IN DISCRIMINANT, LOGIT, AND REGRESSION ANALYSES

2004 ◽  
Vol 03 (02) ◽  
pp. 265-279 ◽  
Author(s):  
STAN LIPOVETSKY ◽  
MICHAEL CONKLIN
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Statistical Models ◽  
Regression Analyses ◽  
Discriminant Functions ◽  
Multivariate Statistical ◽  
Linear Discriminant ◽  
Variable Contribution ◽  
Linear Aggregate

Comparative contribution of predictors in multivariate statistical models is widely used for decision making on the importance of the variables for the aims of analysis and prediction. However, the analysis can be made difficult because of the predictors' multicollinearity that distorts estimates for coefficients in the linear aggregate. To solve the problem of the robust evaluation of the predictors' contribution, we apply the Shapley Value regression analysis that provides consistent results in the presence of multicollinearity both for regression and discriminant functions. We also show how the linear discriminant function can be constructed as a multiple regression, and how the logistic regression can be approximated by linear regression that helps to obtain the variables contribution in the linear aggregate.

Refinements of the maximin approach to decision-making in a fuzzy environment

1996 ◽  
Vol 81 (1) ◽  
pp. 103-122 ◽  
Author(s):  
Didier Dubois ◽  
Hélène Fargier ◽  
Henri Prade
Keyword(s):  
Decision Making ◽  
Fuzzy Environment
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