A5003319227- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Image and Object Detection Techniques
- Advanced Multi-Objective Optimization Algorithms
- Advanced Image and Video Retrieval Techniques
- Image Processing Techniques and Applications
- Medical Image Segmentation Techniques
- Image Enhancement Techniques
- Robotics and Sensor-Based Localization
- Advanced Vision and Imaging
- Image Retrieval and Classification Techniques
- Neural Networks and Applications
- Remote-Sensing Image Classification
- Fuzzy Logic and Control Systems
- Advanced Image Fusion Techniques
- Digital Imaging for Blood Diseases
- Image Processing and 3D Reconstruction
- Distributed Control Multi-Agent Systems
- Advanced Surface Polishing Techniques
- Advanced Image Processing Techniques
- Machine Learning and Algorithms
- Adaptive Control of Nonlinear Systems
- Robotic Path Planning Algorithms
- AI in cancer detection
- Brain Tumor Detection and Classification
Universidad de Guadalajara
2016-2025
Computer Algorithms for Medicine
2018
Doane University
2018
Universidad Técnica del Norte
2018
Universidad de La Frontera
2018
Universidad Antonio Nariño
2018
Universidad de Ingeniería y Tecnología
2018
Center for Research and Advanced Studies of the National Polytechnic Institute
2002-2015
Cultura
2015
Intel (United States)
2006
In this research, the effectiveness of a novel optimizer dubbed as decomposition-based multi-objective symbiotic organism search (MOSOS/D) for problems was explored. The proposed based on organisms’ (SOS), which is star-rising metaheuristic inspired by natural phenomenon symbioses among living organisms. A decomposition framework incorporated in SOS stagnation prevention and its deep performance analysis real-world applications. investigation included both qualitative quantitative analyses...
In this paper, a multilevel thresholding (MT) algorithm based on the harmony search (HSA) is introduced. HSA an evolutionary method which inspired in musicians improvising new harmonies while playing. Different to other algorithms, exhibits interesting capabilities still keeping low computational overhead. The proposed encodes random samples from feasible space inside image histogram as candidate solutions, whereas their quality evaluated considering objective functions that are employed by...
The search for new energy resources is a crucial task nowadays. Research on the use of solar growing every year. aim design devices that can produce considerable amount using Sun’s radiation. modeling cells (SCs) based estimation intrinsic parameters electrical circuits simulate their behavior current vs. voltage characteristics. problem SC defined by highly nonlinear and multimodal objective functions. Most algorithms proposed to find best solutions become trapped into local solutions. This...
The efficient use of energy in electrical systems has become a relevant topic due to its environmental impact. Parameter identification induction motors and capacitor allocation distribution networks are two representative problems that have strong implications the massive energy. From an optimization perspective, both considered extremely complex their non-linearity, discontinuity, high multi-modality. These characteristics make difficult solve them by using standard techniques. On other...
Recently, the resources of renewable energy have been in intensive use due to their environmental and technical merits. The identification unknown parameters photovoltaic (PV) models is one main issues simulation modeling sources. Due random behavior weather, change output current from a PV model nonlinear. In this regard, new optimization algorithm called Runge–Kutta optimizer (RUN) applied for estimating three models. RUN R.T.C France solar cell, as case study. Moreover, root mean square...
A metaheuristic algorithm for global optimization called the collective animal behavior (CAB) is introduced. Animal groups, such as schools of fish, flocks birds, swarms locusts, and herds wildebeest, exhibit a variety behaviors including swarming about food source, milling around central locations, or migrating over large distances in aligned groups. These are often advantageous to allowing them increase their harvesting efficiency, follow better migration routes, improve aerodynamic, avoid...
Swarm intelligence (SI) is a research field which has recently attracted the attention of several scientific communities. An SI approach tries to characterize collective behavior animal or insect groups build search strategy. These methods consider biological systems, can be modeled as optimization processes certain extent. The Social Spider Optimization (SSO) novel swarm algorithm that based on cooperative characteristics social spider. In SSO, agents represent set spiders collectively move...
For various daunting physical world structural optimization design problems, a novel multi-objective water strider algorithm (MOWSA) is proposed, and its non-dominated sorting (NDS) framework explored. This effort inspired by the recent proposals for Water Strider Algorithm, population-based mathematical paradigm focused on lifespan of insects. The crowding distance characteristic integrated into MOSWA to improve exploration exploitation trade-off behavior during advancement quest....
This paper deals with real-time adaptive tracking for discrete-time induction motors in the presence of bounded disturbances. A high-order neural-network structure is used to identify plant model, and based on this a control law derived, which combines block-control sliding-mode techniques. also includes respective stability analysis whole system strategy avoid weight zero-crossing. The scheme implemented real time using three-phase motor.
System identification is a complex optimization problem which has recently attracted the attention in field of science and engineering. In particular, use infinite impulse response (IIR) models for preferred over their equivalent FIR (finite response) since former yield more accurate physical plants real world applications. However, IIR structures tend to produce multimodal error surfaces whose cost functions are significantly difficult minimize. Evolutionary computation techniques (ECT)...
As an alternative to classical techniques, the problem of image segmentation has also been handled through evolutionary methods. Recently, several algorithms based on principles have successfully applied with interesting performances. However, most them maintain two important limitations: (1) they frequently obtain suboptimal results (misclassifications) as a consequence inappropriate balance between exploration and exploitation in their search strategies; (2) number classes is fixed known...