Papers

10

Total Citations

267

H-Index

7

About

Leticia Amador-Angulo is a prominent researcher specializing in fuzzy logic systems, bio-inspired optimization algorithms, and autonomous mobile robot control. Her work consistently bridges the gap between advanced fuzzy theory and practical engineering applications, with a particular focus on dynamically adapting metaheuristic algorithms using increasingly sophisticated fuzzy frameworks. Among her most significant contributions is her pioneering exploration of Type-1, Interval Type-2, Generalized Type-2, and — notably — Interval Type-3 Fuzzy Logic Systems for parameter adaptation in Bee Colony Optimization (BCO), a line of research that has garnered over 94 citations in a single foundational study. Her 2017 comparative analysis of fuzzy-enhanced swarm intelligence methods, including PSO, BCO, and Bat Algorithm, has drawn 61 citations, underscoring the breadth and relevance of her methodological insights. She has further extended her portfolio through investigations into Chicken Search Optimization, Differential Evolution, and Harmony Search for optimal fuzzy controller design. Amador-Angulo's cumulative impact — exceeding 260 citations across a decade of sustained output — reflects her growing influence in computational intelligence. Her research continues to evolve, with recent work refining Sugeno–Takagi interval type-2 systems for stable robot control, affirming her as a forward-thinking voice in intelligent systems research.

Research Focus

Key Achievements

7
H-Index
10
Papers
267
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot
94 citations · 2016
📈 Most Prolific Year: 2016 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Instituto Tecnológico de Tijuana, Tecnológico Nacional de México

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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