Amit Mittal
Papers
1
Total Citations
35
H-Index
1
About
Amit Mittal is an emerging researcher whose work sits at the intersection of computational intelligence, decision science, and fuzzy logic. His most recognized contribution focuses on advancing multi-criteria decision-making frameworks, particularly through the development of novel probabilistic ordered weighted cosine similarity operators within Pythagorean fuzzy environments. Published in 2022, this work addresses complex real-world scenarios where uncertainty and imprecision are inherent in group decision-making processes — a challenge increasingly relevant across fields such as supply chain management, healthcare evaluation, and engineering selection problems. By extending classical similarity measures into probabilistic and Pythagorean fuzzy domains, Mittal's research equips decision-makers with more robust and mathematically rigorous tools for handling ambiguous information. The paper has already garnered 35 citations, signaling meaningful traction within the fuzzy sets and decision analysis research community. His contributions reflect a broader movement toward integrating advanced aggregation operators with uncertainty modeling, and his work serves as a valuable reference for researchers developing intelligent decision support systems. Students exploring fuzzy mathematics or multi-attribute group decision-making will find his methodological innovations both practically applicable and theoretically substantive.
Research Focus
Key Achievements
Top Papers
- 1