Dr. FERNANDO ABRAHAM FAUSTO MARTÍNEZ
Resumen curricular:
El Dr. Fernando Abraham Fausto Martínez recibió el título de Ingeniero en Mecatrónica por parte de la Universidad del Valle de Atemajac (UNIVA) en 2012. Posteriormente, estudió la Maestría en Ciencias en Electrónica y Computación en el Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI) de la Universidad de Guadalajara (UDG), recibiendo el grado de maestro en 2014; así mismo, el Dr. Fausto recibió el grado de Doctor en Ciencias de la Electrónica y la Computación por parte de la misma institución en 2018. Actualmente, el Dr. Fernando Fausto se desempeña como profesor investigador en el CUCEI, y forma parte del cuerpo académico Inteligencia Computacional (UDG-CA-1139), donde realiza investigación relacionada a las líneas de investigación de Sistemas Inteligentes, Aprendizaje de Máquina y Cómputo Metaheurístico. Desde el 2019, el Dr. Fausto es miembro del Sistema Nacional de Investigadores (SNI), teniendo distinción como Investigador Nacional Nivel I.
Perfil de Investigador SNII:
Perfil PRODEP:
Estancia Posdoctoral
Bases de datos bibliográficas:
Publicaciones del académico:
- Detection of COVID-19: A Metaheuristic-Optimized Maximally Stable Extremal Regions Approach
- Inverse Optimal Control Using Metaheuristics of Hydropower Plant Model via Forecasting Based on the Feature Engineering
- Moth swarm algorithm for image contrast enhancement
- A better balance in metaheuristic algorithms: Does it exist? Swarm Evol Comput 54: 100671
- Studies in Computational Intelligence
- Intelligent Systems Reference Library
- Preface
- A better balance in metaheuristic algorithms: Does it exist?
- Comparison of Metaheuristic Methods for Template Matching
- An introduction to nature-inspired metaheuristics and swarm methods
- The locust swarm optimization algorithm
- The selfish herd optimizer
- The swarm method of the social-spider
- Metaheuristics and swarm methods: a discussion on their performance and applications
- Locust search algorithm applied to multi-threshold segmentation
- New Advancements in Swarm Algorithms: Operators and Applications
- Locust search algorithm applied for template matching
- Multimodal Swarm Algorithm Based on the Collective Animal Behavior (CAB) for Circle Detection
- A swarm algorithm inspired by the collective animal behavior
- Auto-calibration of Fractional Fuzzy Controllers by Using the Swarm Social-Spider Method
- From ants to whales: metaheuristics for all tastes
- An improved Simulated Annealing algorithm based on ancient metallurgy techniques
- A Real-Coded Optimal Sensor Deployment Scheme for Wireless Sensor Networks Based on the Social Spider Optimization Algorithm
- A swarm approach for improving voltage profiles and reduce power loss on electrical distribution networks
- Social spider optimization algorithm: modifications, applications, and perspectives
- Ls-II: an improved locust search algorithm for solving optimization problems
- Research Article Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems
- A template matching approach based on the behavior of swarms of locust
- A new descriptor for image matching based on bionic principles
- A global optimization algorithm inspired in the behavior of selfish herds
- A chaos-embedded gravitational search algorithm for the identification of electrical parameters of photovoltaic cells
- A states of matter search-based approach for solving the problem of intelligent power allocation in plug-in hybrid electric vehicles
- An optimization based approach for maximizing the information content of keypoints detected on a digital image
- Research Article Multithreshold Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms
- Multithreshold segmentation by using an algorithm based on the behavior of locust swarms