Daekook Kang
Papers
4
Total Citations
63
H-Index
4
About
Dr. Daekook Kang is a leading researcher in multi-criteria decision-making (MCDM) under uncertainty, with a particular focus on intuitionistic fuzzy sets and their applications in robotics and sustainable systems. His work is distinguished by developing novel decision frameworks that incorporate three critical factors—positive, abstained, and negative grades of membership—enabling more nuanced and realistic evaluations in complex selection problems. Dr. Kang’s most cited paper, "Intuitionistic fuzzy MAUT-BW Delphi method for medication service robot selection during COVID-19" (27 citations), directly addressed the urgent healthcare challenge of deploying robotic systems to reduce viral transmission, demonstrating the real-world impact of his methodologies. He has further advanced the field by introducing centroid and graded mean ranking methods for intuitionistic trapezoidal dense fuzzy sets, specifically tailored for industrial robot selection, and by applying fuzzy decision-making techniques to weed management in agricultural systems (10 citations). Through his innovative integration of fuzzy logic with MCDM tools, Dr. Kang has provided robust solutions for technology selection in healthcare, manufacturing, and agriculture, establishing himself as a key contributor to intelligent decision support systems.
Research Focus
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Top Papers
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