Dr Palash Dutta

@dibru.ac.in

Associate Professor, Dept of Mathematics
Dibrugarh University



              

https://researchid.co/palash

RESEARCH INTERESTS

Fuzzy Set Theory, Decision Making

94

Scopus Publications

1723

Scholar Citations

23

Scholar h-index

44

Scholar i10-index

Scopus Publications






  • Dissimilarity measure on intuitionistic fuzzy sets from an optimistic viewpoint of the information and its diverse applications
    Brindaban Gohain, Surabhi Gogoi, Rituparna Chutia, and Palash Dutta
    Springer Science and Business Media LLC

  • A novel generalized similarity measure under intuitionistic fuzzy environment and its applications to criminal investigation
    Palash Dutta and Abhilash Kangsha Banik
    Springer Science and Business Media LLC
    AbstractIn our contemporary world, where crime prevails, the expeditious conduct of criminal investigations stands as an essential pillar of law and order. However, these inquiries often grapple with intricate complexities, particularly uncertainties stemming from the scarcity of reliable evidence, which can significantly hinder progress. To surmount these challenges, the invaluable tools of crime linkage and psychological profiling of offenders have come to the forefront. The advent of Intuitionistic Fuzzy Sets (IFS) has proven pivotal in navigating these uncertain terrains of decision-making, and at the heart of this lies the concept of similarity measure-an indispensable tool for unraveling intricate problems of choice. While a multitude of similarity measures exists for gauging the likeness between IFSs, our study introduces a novel generalized similarity measure firmly rooted in the IFS framework, poised to surpass existing methods with enhanced accuracy and applicability. We then extend the horizon of practicality by employing this pioneering similarity measure in the domain of clustering for crime prediction-a paramount application within the realm of law enforcement. Furthermore, we venture into the domain of psychological profiling, a potent avenue that has the potential to significantly fortify the arsenal of crime investigations. Through the application of our proposed similarity measure, we usher in a new era of efficacy and insight in the pursuit of justice. In sum, this study not only unveils a groundbreaking similarity measure within the context of an Intuitionistic fuzzy environment but also showcases its compelling applications in the arena of criminal investigation, marking a significant stride toward swifter and more informed decisions in the realm of law and order.



  • Novel distance measure for q-rung orthopair fuzzy sets with application to transportation problem
    Palash Dutta, Bornali Saikia, and Abhilash Kangsha Banik
    Springer Science and Business Media LLC

  • A Novel Weighted Evidence Combination Method Based on Reliability and Credibility degree with an Application in Decision Making Process
    Palash Dutta and Sonom Shome
    World Scientific Pub Co Pte Ltd
    The Dempster–Shafer theory (DST), also known as Belief function theory (BFT), finds extensive application across various domains involving data fusion. However, it is not uncommon to encounter counterintuitive results when combining highly conflicting pieces of evidence using the Dempster combination rule (DCR). While the literature offers several combination rules, only a few address these shortcomings effectively. To address these limitations and rectify the issue of counterintuitive outcomes, a novel weighted evidence fusion rule has been introduced. This fusion approach comprises four key steps: First, the reliability degree of each evidence set, also known as body of evidence (BOE) is determined based on its compatibility degree and total correlation. This step helps to mitigate conflicts arising from unreliable sources. Second, the degree of credibility of each BOE is computed, taking into account distance of evidence and uncertainty degree, further enhancing the accuracy of the fusion process. Third, the reliability and credibility degrees are combined to derive weights for each BOE, ensuring that more weight is assigned to trustworthy sources of evidence. Finally, these weights for each BOE are used to compute a modified Basic Probability Assignment (BPA) for each proposition, which are then fused using the Dempster combination rule. Numerous numerical examples, as well as artificial and real datasets, have been employed to emphasize the effectiveness and potential of this innovative approach. Furthermore, through comparative analysis, it becomes evident that the proposed rule consistently outruns other existing methods, ensuring more accurate and reliable outcomes.


  • Nonlinear distance measures under the framework of Pythagorean fuzzy sets with applications in problems of pattern recognition, medical diagnosis, and COVID-19 medicine selection
    Palash Dutta, Gourangajit Borah, Brindaban Gohain, and Rituparna Chutia
    Springer Science and Business Media LLC
    Abstract Background The concept of Pythagorean fuzzy sets (PFSs) is an utmost valuable mathematical framework, which handles the ambiguity generally arising in decision-making problems. Three parameters, namely membership degree, non-membership degree, and indeterminate (hesitancy) degree, characterize a PFS, where the sum of the square of each of the parameters equals one. PFSs have the unique ability to handle indeterminate or inconsistent information at ease, and which demonstrates its wider scope of applicability over intuitionistic fuzzy sets. Results In the present article, we opt to define two nonlinear distances, namely generalized chordal distance and non-Archimedean chordal distance for PFSs. Most of the established measures possess linearity, and we cannot incorporate them to approximate the nonlinear nature of information as it might lead to counter-intuitive results. Moreover, the concept of non-Archimedean normed space theory plays a significant role in numerous research domains. The proficiency of our proposed measures to overcome the impediments of the existing measures is demonstrated utilizing twelve different sets of fuzzy numbers, supported by a diligent comparative analysis. Numerical examples of pattern recognition and medical diagnosis have been considered where we depict the validity and applicability of our newly constructed distances. In addition, we also demonstrate a problem of suitable medicine selection for COVID-19 so that the transmission rate of the prevailing viral pandemic could be minimized and more lives could be saved. Conclusions Although the issues concerning the COVID-19 pandemic are very much challenging, yet it is the current need of the hour to save the human race. Furthermore, the justifiable structure of our proposed distances and also their feasible nature suggest that their applications are not only limited to some specific research domains, but decision-makers from other spheres as well shall hugely benefit from them and possibly come up with some further extensions of the ideas.

  • An advanced similarity measure for Pythagorean fuzzy sets and its applications in transportation problem
    Bornali Saikia, Palash Dutta, and Pranjal Talukdar
    Springer Science and Business Media LLC






  • Construction of hyperbolic fuzzy set and its applications in diverse COVID-19 associated problems
    Palash Dutta and Gourangajit Borah
    World Scientific Pub Co Pte Ltd
    This paper’s core objective is to introduce a novel notion called hyperbolic fuzzy set (HFS) where, the grades follow the stipulation that the product of optimistic and pessimistic degree must be less than or equal to one (1), rather than their sum not exceeding one (1) as in case of IFSs. The concept of HFS originates from a hyperbola, which provides extreme flexibility to the decision makers in the representation of vague and imprecise information. It is observed that IFSs, Pythagorean fuzzy sets (PFSs), and q-rung orthopair fuzzy sets (Q-ROFSs) often failed to express the uncertain information properly under some specific situations, while HFS tends to overcome such limitations by being applicable under those perplexed situations too. In this paper, we first define some basic operational laws and few desirable properties of HFSs. Second, we define a novel score function, accuracy function, and also establish some of their properties. Third, a novel similarity and distance measure is proposed for HFSs that are capable of distinguishing between different physical objects or alternatives based on the grounds of “similitude degree” and “farness coefficient”, respectively. Later, the advantages of all of these newly defined measures have been showcased by performing a meticulous comparative analysis. Finally, these measures have been successfully applied in various COVID-19 associated problems such as medical decision-making, antivirus face-mask selection, efficient sanitizer selections, and effective medicine selection for COVID-19. The final results obtained with our newly defined measures comply with several other existing methods that we considered and the decision strategy adopted is simple, logical, and efficient. The significant findings of this study are certain to aid the healthcare department and other frontline workers to take necessary measures to reduce the intensity of the coronavirus transmission, so that we can hopefully progress toward the end of this ruthless pandemic.

  • Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers
    Palash Dutta and Gourangajit Borah
    Springer Science and Business Media LLC
    Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have showcased their lack of efficiency and hence eventually it has paved the ways for the development of Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision makers can model most of the real-life phenomena by fuzzy information-based preferences. The availability of a wide literature on similarity measure (SM) emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct accurate and precise decision making in FMCDM problems. Despite having few advantages, most of the existing approaches possessed a certain degree of counter intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately overcome the impediments associated with the earlier existing approaches. Moreover, a meticulous comparative study with the existing approaches is also presented. This paper provides us with an improved method to obtain the similarity values between GTrFNs and the proposed SM consists of calculating the prominent features of fuzzy numbers such as expected value and variance. We use fourteen different sets of GTrFNs, to compare the fruition of the present approach with the existing SM approaches. Furthermore, to show the utility and applicability of our proposed measure, we illustrate few practical scenarios such as the launching of an electronic gadget by a company, a problem of medical diagnosis and finally, a proper anti-virus mask selection in light of the recent COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned FMCDM problems, are analytically correct and they depict the efficiency and novelty of the present article.

  • Hyperbolic Fuzzy TOPSIS Method for Multi-Criteria Decision-Making Problems
    Palash Dutta and Abhilash Kangsha Banik
    Springer International Publishing

  • An Advanced Entropy Measure of IFSs via Similarity Measure
    Pranjal Talukdar and Palash Dutta
    IGI Global
    The Entropy measure of an intuitionistic fuzzy set (IFS) plays a significant role in decision making sciences, for instance, medical diagnosis, pattern recognition, criminal investigation, etc. The inadequate nature of an entropy measure may lead to some invalid results. Therefore, it is significant to use an efficient entropy measure for studying various decision-making problems under IFS environment. This paper first proposes a novel similarity measure for IFS. Based on the proposed similarity measure, an advanced entropy measure is defined with a different axiomatic approach. This axiomatic approach allows us to measure an IFS's entropy with the help of a similarity measure. To show the efficiency of the proposed similarity measure, a comparative study is performed with the existing similarity measures. Some structural linguistic variables are taken as examples to show the validity and consistency of the proposed entropy measure along with the existing entropy measures. Finally, based on the proposed entropy measure, a multi-criteria decision-making problem is performed.

  • Cognitive Decision-Making Based on a Non-linear Similarity Measure Using an Intuitionistic Fuzzy Set Framework
    Pranjal Talukdar, Palash Dutta, and Soumendra Goala
    Springer Science and Business Media LLC


RECENT SCHOLAR PUBLICATIONS

  • Fuzzy risk analysis in crop selection using information measures on quadripartitioned single-valued neutrosophic sets
    G Borah, P Dutta
    Expert Systems with Applications 255, 124750 2024

  • An extended group decision-making algorithm with intuitionistic fuzzy set information distance measures and their applications
    H Garg, D Dutta, P Dutta, B Gohain
    Computers & Industrial Engineering 197, 110537 2024

  • An efficient decision making method based on hyperbolic fuzzy environment with new score function and its application in determining crime prone zones
    AK Banik, P Dutta
    International Journal of Machine Learning and Cybernetics, 1-27 2024

  • New distance measure for intuitionistic fuzzy set and its application in multi-attribute decision-making
    P Dutta, AK Banik
    Strategic Fuzzy Extensions and Decision-making Techniques, 58-81 2024

  • Similarity measure on intuitionistic fuzzy sets based on Benchmark Line and it’s diverse applications
    D Dutta, P Dutta, B Gohain
    Engineering Applications of Artificial Intelligence 133, 108522 2024

  • Multi-criteria group decision-making process using convex combination of q-rung orthopair basic probability assignment with application to medical diagnosis
    H Garg, B Limboo, P Dutta
    Engineering Applications of Artificial Intelligence 133, 108421 2024

  • Quintic fuzzy sets: A new class of fuzzy sets for solving multi-criteria decision-making problems under uncertainty
    P Dutta, A Konwar
    Decision Analytics Journal 11, 100449 2024

  • Dissimilarity measure on intuitionistic fuzzy sets from an optimistic viewpoint of the information and its diverse applications
    B Gohain, S Gogoi, R Chutia, P Dutta
    International Journal of Machine Learning and Cybernetics 15 (6), 2149-2177 2024

  • Novel distance measure for q-rung orthopair fuzzy sets with application to transportation problem
    P Dutta, B Saikia, AK Banik
    International Journal of Information Technology, 1-18 2024

  • A Novel Weighted Evidence Combination Method Based on Reliability and Credibility degree with an Application in Decision Making Process
    P Dutta, S Shome
    New Mathematics and Natural Computation, 1-29 2024

  • A novel approach for arithmetic operations and ranking of generalized fuzzy numbers with application
    P Dutta, B Saikia, G Borah
    Decision Analytics Journal 10, 100428 2024

  • A novel generalized similarity measure under intuitionistic fuzzy environment and its applications to criminal investigation
    P Dutta, AK Banik
    Artificial Intelligence Review 57 (3), 69 2024

  • TWO PARAMETERS EXTENSION OF FUZZY SET: A REVIEW
    AK Banik, P Dutta
    Assam Statistical Review 2024

  • HYPERBOLIC FUZZY RELATIONS AND APPLICATION OF HYPERBOLIC FUZZY MAX-MIN-MAX COMPOSITE RELATION IN MEDICAL DIAGNOSIS
    P Dutta, A Konwar
    Assam Statistical Review 2024

  • Leveraging a New Base Belief Function for Conflict Data Management and Decision Support
    P Dutta, S Shome
     2023

  • Medical Decision-Making and Pattern Recognition Via an Advanced Similarity Measure Based on Single-Valued Neutrosophic Sets
    P Dutta, G Borah
    SN Computer Science 5 (1), 105 2023

  • An advanced similarity measure for Pythagorean fuzzy sets and its applications in transportation problem
    B Saikia, P Dutta, P Talukdar
    Artificial Intelligence Review 56 (11), 12689-12724 2023

  • Crime linkage and psychological profiling of offenders under intuitionistic fuzzy environment using a novel resemblance measure
    P Dutta, AK Banik
    Artificial Intelligence Review 56 (Suppl 1), 893-936 2023

  • New Ranking Approach of Intuitionistic Fuzzy Sets and its Application in Cognitive Transportation Problem
    B Saikia, P Dutta
     2023

  • Erratum: Construction of hyperbolic fuzzy set and its applications in diverse covid-19 associated problems
    P Dutta, G Borah
    New Mathematics and Natural Computation 19 (01), 1-2 2023

MOST CITED SCHOLAR PUBLICATIONS

  • Fuzzy arithmetic with and without using α-cut method: a comparative study
    P Dutta, H Boruah, T Ali
    International Journal of Latest Trends in Computing 2 (1), 99-108 2011
    Citations: 184

  • Some aspects of picture fuzzy set
    P Dutta, S Ganju
    Transactions of A. Razmadze Mathematical Institute 172 (2), 164-175 2018
    Citations: 92

  • Distance measure on intuitionistic fuzzy sets and its application in decision‐making, pattern recognition, and clustering problems
    B Gohain, R Chutia, P Dutta
    International Journal of Intelligent Systems 37 (3), 2458-2501 2022
    Citations: 86

  • Medical Diagnosis Based on Distance Measures Between Picture Fuzzy Sets
    P Dutta
    International Journal of Fuzzy System Applications (IJFSA) 7 (4), 15-36 2018
    Citations: 81

  • Uncertainty modeling in risk assessment based on Dempster–Shafer theory of evidence with generalized fuzzy focal elements
    P Dutta
    Fuzzy information and engineering 7 (1), 15-30 2015
    Citations: 72

  • A New Combination Rule for Conflict Problem of Dempster-Shafer Evidence Theory
    T Ali, P Dutta, H Boruah
    International Journal of Energy, Information and Communications 3 (1), 35-40 2012
    Citations: 62

  • Construction and generation of distance and similarity measures for intuitionistic fuzzy sets and various applications
    B Gohain, P Dutta, S Gogoi, R Chutia
    International Journal of Intelligent Systems 2021
    Citations: 45

  • Modeling of variability and uncertainty in human health risk assessment
    P Dutta
    MethodsX 4, 76-85 2017
    Citations: 45

  • Fuzzy Decision Making in Medical Diagnosis Using an Advanced Distance Measure on Intuitionistic Fuzzy Sets
    P Dutta, S Goala
    The Open Cybernetics & Systemics Journal 12 (2018), 136-149 2018
    Citations: 43

  • An uncertainty measure and fusion rule for conflict evidences of big data via Dempster–Shafer theory
    P Dutta
    International Journal of Image and Data Fusion 9 (2), 152-169 2018
    Citations: 41

  • A q-rung orthopair basic probability assignment and its application in medical diagnosis
    B Limboo, P Dutta
    Decision Making: Applications in Management and Engineering 5 (1), 290-308 2022
    Citations: 40

  • Medical Diagnosis via Distance Measures on Picture Fuzzy Sets
    P Dutta
    ADVANCES IN MODELLING AND ANALYSIS A 54 (2), 137-152 2017
    Citations: 39

  • Arithmetic operations on normal semi elliptic intuitionistic fuzzy numbers and their application in decision-making
    P Dutta, B Saikia
    Granular Computing 6, 163-179 2021
    Citations: 38

  • Bell-shaped fuzzy soft sets and their application in medical diagnosis
    P Dutta, B Limboo
    Fuzzy information and engineering 9 (1), 67-91 2017
    Citations: 35

  • A distance measure for optimistic viewpoint of the information in interval-valued intuitionistic fuzzy sets and its applications
    B Gohain, R Chutia, P Dutta
    Engineering Applications of Artificial Intelligence 119, 105747 2023
    Citations: 34

  • Two new similarity measures for intuitionistic fuzzy sets and its various applications
    B Gohain, R Chutia, P Dutta, S Gogoi
    International Journal of Intelligent Systems 2022
    Citations: 31

  • Fuzzy Multicriteria Decision Making in Medical Diagnosis using an Advanced Distance Measure on Linguistic Pythagorean Fuzzy Sets
    P Talukdar, S Goala, P Dutta, B Limboo
    Annals of Optimization Theory and Practice 2020
    Citations: 30

  • Distance measures for cubic Pythagorean fuzzy sets and its applications to multicriteria decision making
    P Talukdar, P Dutta
    Granular Computing 6, 267-284 2021
    Citations: 27

  • Methods to obtain basic probability assignment in evidence theory
    T Ali, P Dutta
    International Journal of Computer Applications 38 (4), 46-51 2012
    Citations: 27

  • Decision Making in Medical Diagnosis via Distance Measures on Interval Valued Fuzzy Sets
    P Dutta
    International Journal of System Dynamics Applications (IJSDA) 6 (4), 63-83 2017
    Citations: 26