scholarly journals A Review on the Development of Fuzzy Classifiers with Improved Interpretability and Accuracy Parameters

2021 ◽  
Vol 2 (2) ◽  
pp. 1-9
Author(s):  
Farheen Azad ◽  
Keyword(s):  
Fuzzy Set ◽  
Fuzzy System ◽  
Probabilistic Reasoning ◽  
Fuzzy Theory ◽  
Physical World ◽  
Fundamental Aspect ◽  
Fuzzy Classifiers ◽  
Human Thinking ◽  
Interval Type

This review paper of fuzzy classifiers with improved interpretability and accuracy parameter discussed the most fundamental aspect of very effective and powerful tools in form of probabilistic reasoning, The fuzzy logic concept allows the effective realization of ap-proximate, vague, uncertain, dynamic, and more realistic conditions, which is closer to the actual physical world and human thinking. The fuzzy theory has the competency to catch the lack of preciseness of linguistic terms in a speech of natural language. The fuzzy theory provides a more significant competency to model humans like com-mon-sense reasoning and conclusion making to fuzzy set and rules as good membership function. Also, this paper reviews discussed the evaluation of the fuzzy set, type-1, type-2, and interval type-2 fuzzy system from traditional Boolean crisp set logic along with interpretability and accuracy issues in the fuzzy system.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

An Efficient Non-Iterative Method for Computing the Centroid of an Interval Type-2 Fuzzy Set

2021 ◽  
Keyword(s):  
Iterative Method ◽  
Fuzzy Set ◽  
Interval Type

Abstract The authors have requested that this preprint be withdrawn due to author disagreement.

An Extended TOPSIS Method Based on Gaussian Interval Type-2 Fuzzy Set

2019 ◽  
Vol 21 (6) ◽  
pp. 1831-1843
Author(s):  
Huidong Wang ◽  
Jinli Yao ◽  
Jun Yan ◽  
Mingguang Dong
Keyword(s):  
Fuzzy Set ◽  
Topsis Method ◽  
Interval Type
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