Applications of Generalized Fuzzy Divergence Measure in Multi-criteria Decision-Making and Pattern RecognitionPattern Recognition

2016 ◽  
pp. 93-105
Author(s):  
Anshu Ohlan ◽  
Ramphul Ohlan
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Divergence Measure ◽  
Fuzzy Divergence

scholarly journals Unified Fuzzy Divergence Measures with Multi-Criteria Decision Making Problems for Sustainable Planning of an E-Waste Recycling Job Selection

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 90 ◽  
Author(s):  
Pratibha Rani ◽  
Kannan Govindan ◽  
Arunodaya Raj Mishra ◽  
Abbas Mardani ◽  
Melfi Alrasheedi ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Waste Recycling ◽  
Multi Criteria Decision Making ◽  
Divergence Measure ◽  
Divergence Measures ◽  
Job Selection ◽  
Sustainable Planning ◽  
Control Decision ◽  
Fuzzy Divergence

In the literature of information theory and fuzzy set doctrine, there exist various prominent measures of divergence; each possesses its own merits, demerits, and disciplines of applications. Divergence measure is a tool to compute the discrimination between two objects. Particularly, the idea of divergence measure for fuzzy sets is significant since it has applications in several areas viz., process control, decision making, image segmentation, and pattern recognition. In this paper, some new fuzzy divergence measures, which are generalizations of probabilistic divergence measures are introduced. Next, we review two different generalizations of the following measures. Firstly, directed divergence (Kullback–Leibler or Jeffrey invariant) and secondly, Jensen difference divergence, based on these measures, we develop a class of unified divergence measures for fuzzy sets (FSs). Then, a method based on divergence measure for fuzzy sets (FSs) is proposed to evaluate the multi-criteria decision-making (MCDM) problems under the fuzzy atmosphere. Lastly, an illustrative example of the recycling job selection problem of sustainable planning of the e-waste is presented to demonstrate the reasonableness and usefulness of the developed method.

scholarly journals Logarithmic Divergence Measure for Fuzzy Matrix and Application

2021 ◽  
Vol 8 ◽  
pp. 1-20
Author(s):  
Alka Rani ◽  
Omdutt Sharma ◽  
Priti Gupta
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Divergence Measure ◽  
Logarithmic Divergence ◽  
Fuzzy Matrix ◽  
Decision Making Problem ◽  
Fuzzy Divergence

This paper introduces a new divergence measure for a fuzzy matrix with proof of its validity. In addition, the properties are proved for the new fuzzy divergence measure. A method to solve decision making problem is developed by using the proposed fuzzy divergence measure. Finally, the application of this fuzzy divergence measure to decision making is shown using real-life example

scholarly journals An Extended Shapley TODIM Approach Using Novel Exponential Fuzzy Divergence Measures for Multi-Criteria Service Quality in Vehicle Insurance Firms

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1452
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Abbas Mardani ◽  
Reetu Kumari ◽  
Edmundas Kazimieras Zavadskas ◽  
...  
Keyword(s):  
Decision Making ◽  
Service Quality ◽  
Real Life ◽  
Multicriteria Decision Making ◽  
Divergence Measure ◽  
Divergence Measures ◽  
Shapley Function ◽  
Service Quality Evaluation ◽  
Segmentation Pattern ◽  
Fuzzy Divergence

Classification of the divergence measure for fuzzy sets (FSs) has been a successful approach since it has been utilized in several disciplines, e.g., image segmentation, pattern recognition, decision making, etc. The objective of the manuscript is to show the advantage of the combined methodology. A comparison clearly shows the usefulness of the proposed technique over the existing ones under the fuzzy environment. This study presents novel exponential-type divergence measures with some elegant features, which can be applied to FSs. Next, a TODIM (an acronym in Portuguese for Interactive Multicriteria Decision Making) approach derived from prospect theory, Shapley function, and divergence measure for multi-criteria decision-making (MCDM) is proposed. Besides, for the reason of evaluating the dominance degree of the option, and the weights of the criteria, proposed divergence measures are implemented. Evaluating and selecting the service quality is the most important issue in management; it has a direct influence on the way the manufacturer performs its tasks. Selecting the service quality can be thought of as a problem of MCDM involving numerous contradictory criteria (whether of a quantitative or qualitative nature) for the evaluation processes. In recent years, the service quality assessment is becoming increasingly complex and uncertain; as a result, some criteria assessment processes cannot be efficiently done by numerical assessments. In addition, decision experts (DEs) may not always show full rationality in different real-life situations that need decision making. Here, a real service quality evaluation problem is considered to discuss the efficacy of the developed methods. The algorithm (TODIM based on the Shapley function and divergence measures) has a unique procedure among MCDM approaches, which is demonstrated for the first time in this paper.

New generalized intuitionistic fuzzy divergence measure with applications to multi-attribute decision making and pattern recognition

2020 ◽  
Vol 13 ◽  
Author(s):  
Adeeba Umar ◽  
Ram Naresh Saraswat
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Intuitionistic Fuzzy Sets ◽  
The Other ◽  
Divergence Measure ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Prime Objective ◽  
Fuzzy Divergence

Background: The notion of fuzzy set was introduced by Zadeh. After that, many researchers extended the concept of fuzzy sets in different ways. Atanassov introduced the concept of intuitionistic fuzzy sets as an extension of fuzzy sets. This concept is applied in many fields such as bio-informatics, image processing, decision making, feature selection, pattern recognition etc. Objectives: The prime objective of this paper is to introduce a new generalized intuitionistic fuzzy divergence measure with proof of its validity and discussions on its elegant properties. Applications of the proposed divergence measure in multi-attribute decision making and pattern recognition are also discussed with some numerical illustrations. Further, the proposed divergence measure is compared with other methods for solving MADM and pattern recognition problems which exist in the literature. Methods: Divergence measure method is used to measure the divergence between two given sets. Also, the results of the other existing measures are also given to compare with the proposed measure. Results: We see that our proposed divergence measure found much better results in comparison with the other existing methods. Conclusion: A new divergence measure for intuitionistic fuzzy sets is introduced with some of its properties. Applications of the proposed divergence measure to pattern recognition and MADM are illustrated through examples. The comparison of the proposed method with the existing methods shows the legacy of the results of the proposed method. It is concluded that the proposed divergence measure is effective for solving real world problems related to MADM and pattern recognition.

Sign in / Sign up

Export Citation Format

Share Document