His primary areas of study are Mathematical optimization, Fuzzy logic, Fuzzy number, Pythagorean fuzzy sets and Pythagorean theorem. Harish Garg has included themes like Intuitionistic fuzzy, Algorithm, Series and Degree in his Mathematical optimization study. His study on Soft set is often connected to Measure as part of broader study in Fuzzy logic.
His study in Fuzzy number is interdisciplinary in nature, drawing from both Discrete mathematics, Fuzzy set operations and Fuzzy classification. His Pythagorean fuzzy sets study combines topics from a wide range of disciplines, such as Interval valued and Operations research. His studies examine the connections between Pythagorean theorem and genetics, as well as such issues in Generalized mean, with regards to Square.
His scientific interests lie mostly in Mathematical optimization, Fuzzy logic, Intuitionistic fuzzy, Fuzzy set and Fuzzy number. His work carried out in the field of Mathematical optimization brings together such families of science as TOPSIS and Degree. His biological study spans a wide range of topics, including Pythagorean theorem, Reliability and Computational intelligence.
His Intuitionistic fuzzy study also includes
The scientist’s investigation covers issues in Fuzzy logic, Fuzzy set, Mathematical optimization, Computational intelligence and Group decision-making. His work on Fuzzy number as part of general Fuzzy logic research is frequently linked to Operator, bridging the gap between disciplines. His research in Fuzzy set intersects with topics in Multiple-criteria decision analysis, Data mining and Extension.
His work deals with themes such as Intuitionistic fuzzy, TOPSIS, Membership function, Vagueness and Fuzzy soft set, which intersect with Mathematical optimization. The study incorporates disciplines such as Soft set and Algorithm in addition to Intuitionistic fuzzy. The various areas that Harish Garg examines in his Computational intelligence study include Ranking, Relation, Variable and Real number.
The scientist’s investigation covers issues in Fuzzy logic, Fuzzy set, Measure, Group decision-making and Operator. His studies in Fuzzy logic integrate themes in fields like Pythagorean theorem, Mathematical optimization, Computational intelligence and Decision analysis. The Mathematical optimization study combines topics in areas such as Soft set, TOPSIS and Group.
His Fuzzy set research includes elements of Range, Multiple-criteria decision analysis, Theoretical computer science and Probabilistic logic. His Multiple-criteria decision analysis study which covers Algorithm that intersects with Hausdorff space, Distance measures and Pattern recognition. The concepts of his Degree study are interwoven with issues in Ranking, Aggregate and Interval valued.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A New Generalized Pythagorean Fuzzy Information Aggregation Using Einstein Operations and Its Application to Decision Making
Journal of intelligent systems (2016)
A hybrid PSO-GA algorithm for constrained optimization problems
Applied Mathematics and Computation (2016)
A Novel Correlation Coefficients between Pythagorean Fuzzy Sets and Its Applications to Decision-Making Processes
Journal of intelligent systems (2016)
Generalized Pythagorean Fuzzy Geometric Aggregation Operators Using Einstein t‐Norm and t‐Conorm for Multicriteria Decision‐Making Process
International Journal of Intelligent Systems (2017)
A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems
soft computing (2016)
Multi-objective reliability-redundancy allocation problem using particle swarm optimization
Harish Garg;S. P. Sharma.
Computers & Industrial Engineering (2013)
A novel accuracy function under interval-valued Pythagorean fuzzy environment for solving multicriteria decision making problem
Journal of Intelligent and Fuzzy Systems (2016)
Generalized intuitionistic fuzzy interactive geometric interaction operators using Einstein t-norm and t-conorm and their application to decision making
Computers & Industrial Engineering (2016)
TOPSIS method based on the connection number of set pair analysis under interval-valued intuitionistic fuzzy set environment
Kamal Kumar;Harish Garg.
Computational & Applied Mathematics (2018)
Linguistic Pythagorean fuzzy sets and its applications in multiattribute decision‐making process
International Journal of Intelligent Systems (2018)
Profile was last updated on December 6th, 2021.
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