Decision making and Uznadzian set theory

1976 ◽  
Author(s):  
Youssef Sabry
Keyword(s):  
Decision Making ◽  
Set Theory

Soft Set-Based Switching Faults Decision Making in DTC Induction Motor Drives

2014 ◽  
Vol 24 (02) ◽  
pp. 1550021 ◽  
Author(s):  
Veli Türkmenoğlu ◽  
Mustafa Aktaş ◽  
Serkan Karataş ◽  
Halil İbrahim Okumuş
Keyword(s):  
Decision Making ◽  
Fault Detection ◽  
Induction Motor ◽  
Set Theory ◽  
Wavelet Decomposition ◽  
Motor Drives ◽  
Soft Set ◽  
Fault Detection And Diagnosis ◽  
Induction Motor Drives ◽  
Detection Mechanism

This paper introduces a method for detection and identification of IGBT-based drive open-circuit fault of DTC induction motor drives. The detection mechanism is based on soft set theory and wavelet decomposition, if it is detailed, ⊼-product decision making method and sym2 wavelet decomposition have been used in the detection mechanism. In this method, the stator currents have been used as an input to the system. The stator current has been used for the detection of the fault. The signal analysis has been performed up to the six level details wavelets decomposition. Faulty switch is detected by applying soft set theory to sixth level wavelets transformation. This is the first time applied to inverter in induction motor drives fault detection. The results demonstrate that the proposed fault detection and diagnosis system has very good capabilities.

A Novel Hybrid Clustering Method for Multi-Attribute Decision-Making Datasets

2012 ◽  
Vol 482-484 ◽  
pp. 103-108
Author(s):  
Kai Ping Liu ◽  
Wen Chin Chen ◽  
Ting Cheng Chang
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Rough Set ◽  
Fuzzy Set Theory ◽  
Uncertain Data ◽  
Clustering Method ◽  
Hybrid Scheme ◽  
Index Function ◽  
Single Attribute ◽  
Multi Attribute Decision Making

A function is proposed for descritizing and classifying the uncertain data of multi-attribute decision-making (MADM) datasets using a hybrid scheme incorporating fuzzy set theory, Rough Set (RS) theory and a modified form of the PBMF index function. The proposed MADM index function is used to extend the applicability of the single-attribute decision-making (SADM) function. The validity of the proposed MADM index function is evaluated by comparing the descritizing results obtained for a simple hypothetical function with those obtained using a SADM function and the conventional PBMF function.

A User-Centered Medical Device Design Decision Making Approach Using Hybrid Rough Cooperative Game Model

2021 ◽  
Author(s):  
Liting Jing ◽  
Junfeng Ma
Keyword(s):  
Decision Making ◽  
Medical Device ◽  
Set Theory ◽  
Cooperative Game ◽  
Rough Set ◽  
Rough Set Theory ◽  
Design Decision ◽  
Device Design ◽  
Medical Device Design ◽  
User Centered

Abstract With the advancement of new technologies and diverse customer-centered design requirements, the medical device design decision making becomes challenge. Incorporating multiple stakeholders’ requirements into the medical device design will significantly affect the market competitiveness and performance. The classic design decision making approaches mainly focused on design criteria priority determination and conceptual schemes evaluation, which lack the capacity of reflecting the interdependence of interest among stakeholders and capturing the ambiguous influence on the overall design expectations, leading to the unreliable decision making results. In order to relax these constraints in the medical device design, this paper incorporates rough set theory with cooperative game theory model to develop a novel user-centered design decision making framework. The proposed approach is composed of three components: 1) end/professional user needs identification and classification, 2) evaluation criteria correlation diagram and scheme value matrix establishment using rough set theory; and 3) fuzzy coalition utility model development to obtain optimal desirability considering users’ conflict interests. We used a blood pressure meter case study to demonstrate and validate the proposed approach. Compared with the traditional Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, the proposed approach is more robust.

An approach to evaluation of emergency plans for unconventional emergency events based on soft fuzzy rough set

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 461-473 ◽  
Author(s):  
Sun Bingzhen ◽  
Ma Weimin
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Management Decision ◽  
Fuzzy Rough Set ◽  
Emergency Plans ◽  
Content Type ◽  
Emergency Events

Purpose – The purpose of this paper is to present a new method for evaluation of emergency plans for unconventional emergency events by using the soft fuzzy rough set theory and methodology. Design/methodology/approach – In response to the problems of insufficient risk identification, incomplete and inaccurate data and different preference of decision makers, a new model for emergency plan evaluation is established by combining soft set theory with classical fuzzy rough set theory. Moreover, by combining the TOPSIS method with soft fuzzy rough set theory, the score value of the soft fuzzy lower and upper approximation is defined for the optimal object and the worst object. Finally, emergency plans are comprehensively evaluated according to the soft close degree of the soft fuzzy rough set theory. Findings – This paper presents a new perspective on emergency management decision making in unconventional emergency events. Also, the paper provides an effective model for evaluating emergency plans for unconventional events. Originality/value – The paper contributes to decision making in emergency management of unconventional emergency events. The model is useful for dealing with decision making with uncertain information.

Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA)

2005 ◽  
Vol 13 (1) ◽  
pp. 23-56 ◽  
Author(s):  
Badredine Arfi
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Trust And Power

In this article I use linguistic fuzzy-set theory to analyze the process of decision making in politics. I first introduce a number of relevant elements of (numerical and linguistic) fuzzy-set theory that are needed to understand the terminology as well as to grasp the scope and depth of the approach. I then explicate a linguistic fuzzy-set approach (LFSA) to the process of decision making under conditions in which the decision makers are required to simultaneously satisfy multiple criteria. The LFSA approach is illustrated through a running (hypothetical) example of a situation in which state leaders need to decide how to combine trust and power to make a choice on security alignment.

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