Dr. DANIEL ZALDÍVAR NAVARRO
Resumen curricular:
Daniel Zaldivar is a Professor at Universidad de Guadalajara, Mexico at Campus Science & Engineering, CUCEI since 1996. Professor Zaldivar has teach IA in the bachelor of computer sciences, the master and doctorate of electronics and computer science. He is a member of the Mexican national science council of the CONACYT, SNI level II. He granted his Ph.D. at Freie Universität Berlin, Germany, in the area of researching and developing autonomous biped robots. At the current time, Professor Zaldivar specializes in the development of new metaheuristic algorithms applied in the optimization of structures of electric-human powered (hybrid) vehicles. He has more than 4500 citations and has achieved h-index 35. Professor Zaldivar has registered three patents in the area.
Perfil de Investigador SNII:
Perfil PRODEP:
Bases de datos bibliográficas:
Publicaciones del académico:
- Pole and Slot Configurations for Efficient Brushless Permanent Magnet Motors
- Prototyping
- Basic Concepts of Motors
- 2D Sketching in CAD Software for 3D Printing
- Fundamentals of Electromagnetism
- Setting up a 3D Model for a 3D Printer
- Differential Evolution Search Strategy Enhancement Through Evolutionary Game Theory
- A metaheuristic algorithm based on a radial basis function neural networks
- Social influence dynamics for image segmentation: a novel pixel interaction approach
- Mathematical Optimization Strategy for Effectiveness Profile Estimation in Two-Dose Vaccines and Its Use in Designing Improved Vaccination Strategies Focused on Pandemic …
- An initialization approach for metaheuristic algorithms by using Gibbs sampling
- New Metaheuristic Schemes: Mechanisms and Applications
- Enhancing Pneumonia Segmentation in Lung Radiographs: A Jellyfish Search Optimizer Approach
- Image segmentation by agent-based pixel homogenization
- Layer dependent changes of neural activity underlying laminar fMRI
- Dynamic Multimodal Function Optimization: An Evolutionary-Mean Shift Approach
- Trajectory-Driven Metaheuristic Approach Using a Second-Order Model
- Multi-objective Optimization of Anisotropic Diffusion Parameters for Enhanced Image Denoising
- Exploring the Potential of Agent Systems for Metaheuristics
- Collaborative Hybrid Grey Wolf Optimizer: Uniting Synchrony and Asynchrony
- Introduction to Metaheuristic Schemes: Characteristics, Properties, and Importance in Solving Optimization Problems
- Efficient Image Contrast Enhancement by Using the Moth Swarm Algorithm
- Studies in Computational Intelligence
- A Review of the Use of Quasi-random Number Generators to Initialize the Population in Meta-heuristic Algorithms
- Neuromodulatory ascending systems: Their influence at the microscopic and macroscopic levels
- Brain-wide functional connectivity of face patch neurons during rest
- An agent-based transmission model of COVID-19 for re-opening policy design
- An improved multi-population whale optimization algorithm
- Solving Reality-Based Trajectory Optimization Problems with Metaheuristic Algorithms Inspired by Metaphors
- An optimized Kernel Extreme Learning Machine for the classification of the autism spectrum disorder by using gaze tracking images
- Metaheuristic schemes and machine learning techniques: A synergistic perspective
- Toward next-generation primate neuroscience: a collaboration-based strategic plan for integrative neuroimaging
- Population management in metaheuristic algorithms: Could less be more?
- Integrating Metaheuristic Algorithms and Minimum Cross Entropy for Image Segmentation in Mist Conditions
- Image Classification with Convolutional Neural Networks
- Thresholding algorithm applied to chest X-ray images with pneumonia
- Cross Entropy Based Thresholding Segmentation of Magnetic Resonance Prostatic Images Using Metaheuristic Algorithms
- Hyperparameter optimization in a convolutional neural network using metaheuristic algorithms
- Kernel recursive least square approach for power system harmonic estimation
- Group-based synchronous-asynchronous grey wolf optimizer
- Learning classical and metaheuristic optimization techniques by using an educational platform based on LEGO robots
- Future urban seismic risk scenarios using a cellular automata model
- An efficient Harris hawks-inspired image segmentation method
- An improved clustering method based on biological visual models
- A novel hybrid metaheuristic optimization method: hypercube natural aggregation algorithm
- A better balance in metaheuristic algorithms: Does it exist?
- Reducing overlapped pixels: a multi-objective color thresholding approach
- Side-blotched lizard algorithm: a polymorphic population approach
- Micro-Grooved Pipe Design of Parabolic Trough by Metaheuristic Optimization: An Empirical Comparison
- Analysis of social vulnerability to natural risk using multivariate statistical techniques