DR. MARIO ALBERTO NAVARRO VELÁZQUEZ
Resumen curricular:
Soy un investigador doctorado en Ciencias de la Electrónica y Computación con orientación en control automático y sistemas inteligentes, especializado en el campo de los algoritmos metaheurísticos y sus aplicaciones. A lo largo de mi carrera, he generado una producción de diversos artículos científicos en áreas como el diseño, la hibridación, la mejora de algoritmos metaheurísticos y el diseño de hiper-heurísticas para resolver problemas de optimización en el diseño ingenieril, asi como aplicaciones para segmentación de imágenes. Mis contribuciones han sido aceptadas en revistas científicas indexadas en el Journal Citation Reports (JCR). Además, he tenido el privilegio de presentar algunos de mis trabajos en importantes conferencias, como en el congreso: Applications of Evolutionary Computation: 25th European Conference, EvoApplications 2022 celebrado en Madrid, España, el IEEE World Congress on Evolutionary Computation 2022 en Padua, Italia y el IEEE World Congress on Evolutionary Computation 2023 celebrado en Chicago, IL, USA, entre otros. Para ampliar mi alcance y compartir conocimientos, he tenido el privilegio de contribuir a capítulos de libros científicos, donde he podido compartir mis investigaciones y perspectivas con otros expertos en la materia.
Perfil de Investigador SNII:
Bases de datos bibliográficas:
Publicaciones del académico:
- A Comparative Analysis of Recent Metaheuristic Algorithms for Image Segmentation Using the Minimum Cross-Entropy for Multilevel Thresholding
- The Age of AI Responsibility: Towards Human-Centric and Ethical Swarm Intelligence
- Improving the exploitation in the estimation of distribution algorithm through simulated annealing strategies for solar energy problems
- Diversity Measurement in Different PSO Variants Applied to Global Optimization and Classical Engineering Problems
- Addressing Limitations and Inaccuracy of Diversity Metrics in Evolutionary Algorithms with an Accurate Dimension-Wise Diversity
- Diversity Measurement in Different PSO Variants Applied to Global Optimization and Classical Engineering Problems
- Metaheuristic Algorithms for Data Clustering in Multivariate Data Sets: A Comparative Analysis
- Optimization of Radial Distribution Networks Through an Improved African Vulture Optimization Algorithm
- Grouping and Partitioning Methods in Metaheuristic Algorithms
- Grouping and Partitioning Methods in Metaheuristic Algorithms
- Grouping and Partitioning Methods in Metaheuristic Algorithms
- Optimization of Radial Distribution Networks Through an Improved African Vulture Optimization Algorithm
- Grouping and Partitioning Methods in Metaheuristic Algorithms
- Optimization of Radial Distribution Networks Through an Improved African Vulture Optimization Algorithm
- Diversity Measurement in Different PSO Variants Applied to Global Optimization and Classical Engineering Problems
- Quasi-random Fractal Search (QRFS): A dynamic metaheuristic with sigmoid population decrement for global optimization
- Metaheuristic optimization with dynamic strategy adaptation: An evolutionary game theory approach
- Handling the balance of operators in evolutionary algorithms through a weighted Hill Climbing approach
- Prism refraction search: a novel physics-based metaheuristic algorithm
- Adaptability and Efficiency in Population Management: A multi-population CMA-ES Strategy for High-Dimensional Optimization
- Population of Hyperparametric Solutions for the Design of Metaheuristic Algorithms: An Empirical Analysis of Performance in Particle Swarm Optimization
- Population of Hyperparametric Solutions for the Design of Metaheuristic Algorithms: An Empirical Analysis of Performance in Particle Swarm Optimization
- Population of Hyperparametric Solutions for the Design of Metaheuristic Algorithms: An Empirical Analysis of Performance in Particle Swarm Optimization
- Population of Hyperparametric Solutions for the Design of Metaheuristic Algorithms: An Empirical Analysis of Performance in Particle Swarm Optimization
- Segmentation of thermographies from electronic systems by using the global-best brain storm optimization algorithm
- An improved opposition-based Runge Kutta optimizer for multilevel image thresholding
- An analysis on the performance of metaheuristic algorithms for the estimation of parameters in solar cell models
- Improving Metaheuristic Algorithm Design Through Inequality and Diversity Analysis: A Novel Multi-Population Differential Evolution
- An Hyper-Heuristic Based Population Management Through Statistical Analysis and Phases Optimization
- A Novel Diversity-Aware Inertia Weight and Velocity Control for Particle Swarm Optimization
- Improving the Convergence of the PSO Algorithm with a Stagnation Variable and Fuzzy Logic
- A Review of the Use of Quasi-random Number Generators to Initialize the Population in Meta-heuristic Algorithms
- Handling stagnation through diversity analysis: A new set of operators for evolutionary algorithms
- Improving the optimization performance by an adaptable design: A dynamic selection of operators via criteria-based matrix for evolutionary algorithms
- Studies in Computational Intelligence
- Improving the Convergence and Diversity in Differential Evolution Through a Stock Market Criterion
- An improved multi-population whale optimization algorithm
- Population management in metaheuristic algorithms: Could less be more?
- Metaheuristics in Machine Learning: Theory and Applications
- Failure detection on electronic systems using thermal images and metaheuristic algorithms
- Side-Blotched Lizard Algorithm: A polymorphic population approach
- Applications of Hybrid Metaheuristic Algorithms for Image Processing
- Comparison of recent metaheuristic algorithms for shape detection in images