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Proceedings ArticleDOI

Soft computing decision making system to analyze the risk factors of T2DM

24 Jun 2019-Vol. 2112, Iss: 1, pp 020086
TL;DR: In this article, a novel decision making system is designed by combining the salient features of The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy Cognitive Map (FCM).
Abstract: Type-2 Diabetes mellitus is one of the most alarming diseases in both developed and developing countries. The WHO predicted that 90% of people around the globe will suffer from T2DM (WHO, 2016). Most of the people are living in India without knowing that they are affected with T2DM. So, the undiagnosed T2DM leads to the complication in heart, kidney disease, eye and feet. Even though Type 2 diabetes has many risk factors associated to it, lifestyle changes play a vital role in triggering the Type 2 diabetes. Hence, the objective of the present study is to analyze and identify the most influencing risk factors of T2DM. Determining the most influencing risk factor of T2DM is not an easy task as there are lot of complexity and uncertainty involved in it. To tackle this issue, a novel decision making system is designed by combining the salient features of The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy Cognitive Map (FCM). Eight risk factors are chosen as the input variables for the system. The proposed system elucidates that Blindness, Obesity, Physical Inactivity are the most influencing factors for the type 2 diabetes mellitus.
Citations
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Book ChapterDOI
01 Jan 2021
TL;DR: This present study analyzes the solid waste management through the Haar FCM with DEMATEL technique to sustain economic growth and better quality of life.
Abstract: An interesting attempt is taken to form a hybrid model by integrating Fuzzy Cognitive Map (FCM), the Delphi Method, and the DEMATEL method through the Haar ranking of Hexagonal Fuzzy Number. To examine this model, the problem of solid waste management is taken. Solid waste arises from human and animal activities can generate major health problems and horrible living environment when they are not dumped of safely and appropriately. The proper disposal of solid waste helps to reduce the terrible impacts on both human health and environment to sustain economic growth and better quality of life. Therefore, this present study analyzes the solid waste management through the Haar FCM with DEMATEL technique.

14 citations

Journal ArticleDOI
TL;DR: In this article , Haar fuzzy DEMATEL method can be proposed using trapezoidal fuzzy number and Haar ranking for analyzing the climate change, which can be applied successfully in the crisp environment, it is not able to deal the situations when the data is full of uncertain and vagueness.
Abstract: Multiple Criteria/Attribute Decision Making (MCDM) models are often used to solve various decision making and selection problems. There are well known methods for solving MCDM problems such as AHP, DEMATEL, TOPSIS, VIKOR, etc., have been developed by the soft computing researchers. Though the DEMATEL method is applied successfully in the crisp environment, it is not able deal the situations when the data is full of uncertain and vagueness. Therefore, Haar fuzzy DEMATEL method can be proposed using trapezoidal fuzzy number and Haar ranking for analyzing the climate change.
References
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Journal ArticleDOI
TL;DR: A fuzzy causal algebra for governing causal propagation on FCMs is developed and it allows knowledge bases to be grown by connecting different FCMs.
Abstract: Fuzzy cognitive maps (FCMs) are fuzzy-graph structures for representing causal reasoning. Their fuzziness allows hazy degrees of causality between hazy causal objects (concepts). Their graph structure allows systematic causal propagation, in particular forward and backward chaining, and it allows knowledge bases to be grown by connecting different FCMs. FCMs are especially applicable to soft knowledge domains and several example FCMs are given. Causality is represented as a fuzzy relation on causal concepts. A fuzzy causal algebra for governing causal propagation on FCMs is developed. FCM matrix representation and matrix operations are presented in the Appendix.

3,116 citations

Book ChapterDOI
01 Jan 1981
TL;DR: There are some classical decision rules such as dominance, maximin and maximum which are still fit for the MADM environment but they do not require the DM’s preference information, and accordingly yield the objective (vs. subjective) solution.
Abstract: There are some classical decision rules such as dominance, maximin and maximum which are still fit for the MADM environment. They do not require the DM’s preference information, and accordingly yield the objective (vs. subjective) solution. However, the right selection of these methods for the right situation is important. (See Table 1.3 for references).

1,890 citations

Journal ArticleDOI
TL;DR: In this article, a hierarchical multiple criteria decision-making (MCDM) model based on fuzzy-sets theory is proposed to deal with the supplier selection problems in the supply chain system.

1,559 citations

Journal ArticleDOI
TL;DR: This model is applicable for defuzzification within the MCDM model with a mixed set of crisp and fuzzy criteria, and a newly developed CFCS method is based on the procedure of determining the left and right scores by fuzzy min and fuzzy max, respectively, and the total score is determined as a weighted average according to the membership functions.
Abstract: In many cases, criterion values are crisp in nature, and their values are determined by economic instruments, mathematical models, and/or by engineering measurement. However, there are situations when the evaluation of alternatives must include the imprecision of established criteria, and the development of a fuzzy multicriteria decision model is necessary to deal with either "qualitative" (unquantifiable or linguistic) or incomplete information. The proposed fuzzy multicriteria decision model (FMCDM) consists of two phases: the CFCS phase - Converting the Fuzzy data into Crisp Scores, and the MCDM phase - MultiCriteria Decision Making. This model is applicable for defuzzification within the MCDM model with a mixed set of crisp and fuzzy criteria. A newly developed CFCS method is based on the procedure of determining the left and right scores by fuzzy min and fuzzy max, respectively, and the total score is determined as a weighted average according to the membership functions. The advantage of this defuzzification method is illustrated by some examples, comparing the results from three considered methods.

625 citations

Journal ArticleDOI
TL;DR: The fuzzy multi-criteria decision-making (MCDM) method is applied to determine the importance weights of evaluation criteria and to synthesize the ratings of candidate aircraft to help the Air Force Academy in Taiwan choose optimal initial training aircraft in a fuzzy environment.
Abstract: This paper develops an evaluation approach based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), to help the Air Force Academy in Taiwan choose optimal initial training aircraft in a fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterised by triangular fuzzy numbers. This study applies the fuzzy multi-criteria decision-making (MCDM) method to determine the importance weights of evaluation criteria and to synthesize the ratings of candidate aircraft. Aggregated the evaluators' attitude toward preference; then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. This approach is demonstrated with a real case study involving 16 evaluation criteria, seven initial propeller-driven training aircraft assessed by 15 evaluators from the Taiwan Air Force Academy.

580 citations