Conjuntos de datos
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Evolutionary Training of Deep Belief Networks for Handwritten Digit Recognition
Two of the most representative deep architectures are Deep Convolutional Neural Networks and Deep Belief Networks (DBNs).Both of these can be applied to the problem of pattern... -
Blood Vessel Analysis on High Resolution Fundus Retinal Images
Image analysis is a relevant tool to improve the healthcare services. Fundus retinal image analysis allows the early detection of ophthalmic diseases such as diabetes and... -
An evolutionary algorithm of linear complexity: application to training of de...
The performance of deep neural networks, such as Deep Belief Networks formed by Restricted Boltzmann Machines (RBMs), strongly depends on their training, which is the process of... -
On the selection of the optimal topology for particle swarm optimization: a s...
In this paper, we deal with the problem of selecting the best topology in Particle Swarm Optimization. Unlike most state-of-the-art papers, where statistical analysis of a large... -
Comparison of Parallel Versions of SA and GA for Optimizing the Performance o...
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving... -
Industrial and Robotic Systems: LASIRS 2019
This work presents a solution of the problem of controlling an industrial robotic system based on visual information received from a stereo camera that monitors robots workcell.... -
Computation of the improvement directions of the Pareto front and its applica...
This paper introduces the mathematical development and algorithm of the Improvement-Directions Mapping (IDM) method, which computes improvement directions to "push" the current... -
Kinematic and dynamic design and optimization of a parallel rehabilitation robot
In this paper, a method for concurrent optimum design of a complex parallel manipulator is introduced. The manipulator is a three-degree-of-freedom mechanism used as a walking... -
The improvement direction mapping method
The Improvement Direction Mapping (IDM) is a novel multi-objective local-search method, that independently steers a solution set towards promising regions by computing... -
A two-stage mono-and multi-objective method for the optimization of general U...
This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a... -
Impact of the COVID-19 lockdown on air quality and resulting public health be...
Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes... -
Efficient training of deep learning models through improved adaptive sampling
Training of Deep Neural Networks (DNNs) is very computationally demanding and resources are typically spent on training-instances that do not provide the most benefit to a... -
Robust parameter estimation of a PEMFC via optimization based on probabilisti...
Recent developments in maintenance modelling fuelled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive... -
Parameter Calibration of the Patch Growing Algorithm for Urban Land Change Si...
Urban growth modelling is a current trend in geo-computation due to its impact on the local living environment and the quality of life. The FUTure Urban-Regional Environment... -
On the best-performed time window size for homicide count forecasting
In the last two decades, violence and homicides have been consistently increasing in Mexico; the official data shows relations to other crimes and time-dependent territorial... -
Spatio-temporal interpolation of rainfall data in western Mexico
One of the most common problems related to meteorological information is the missing registers. This lack of data generates uncertainties in the analysis of climate, hydrology,... -
Automated dimensional synthesis of a portable sky scanner for measuring light...
Light pollution is often measured by a photometric sensor network distributed in the area of interest. However, photometric sensors usually have a narrow view angle, making... -
Mechatronic design of a planar robot using multiobjective optimization
The concurrent design optimization of robots refers to the problem of optimizing parameters that affects different kinds of features at the same time. For instance, this work... -
Evaluación comparativa de algoritmos de predicción aplicados al conteo de hom...
Este trabajo de investigación analiza el impacto de las elecciones subnacionales de 2021 en México en los niveles de homicidios dolosos. Se utilizaron series de tiempo... -
A self-validating method via the unification of multiple models for consisten...
Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision... -
A reaction–convection–diffusion model for PEM fuel cells
In this paper, we present a novel 1D singularly perturbed reaction–convection–diffusion mathematical model, with non-linear coefficients (SP-RCD model), for the physical... -
A Broyden-based algorithm for multi-objective local-search optimization
In multi-objective optimization, the direction vectors in the objective space that improve the current non-dominated set are named improvement directions. The Improvement... -
Estimación de datos faltantes de temperatura combinando IDW y una serie trunc...
Objetivo. Estimar los datos faltantes de la precipitación media mensual en el departamento de Casanare. Metodología. Se revisó la información de estaciones climatológicas... -
Homicide forecasting for the state of Guanajuato using LSTM and geospatial in...
In the last years, intentional homicides have increased significantly in Mexico. A proven strategy to confront the problem is applying predictive methods used to anticipate the... -
Roughness Parameter Estimation for flood numerical simulation using Different...
A methodology to estimate parameters necessary to carry out numerical simulations of flood phenomena is presented, that may be useful for detecting flood-prone areas. Geospatial... -
Improving Geomorphological Classification via Binary Image Processing
Landform classification is the basis for understanding and describing the processes and evolution of landscape. This process usually requires elevation information from... -
Consumo de agua industrial en el Bajío: un análisis por Zona Metropolitana, 2...
It is a characteristic of the condition of the human being, its sense of social interrelation since there is historical evidence that prehistoric person grouped and organized... -
Design optimization and parameter estimation of a PEMFC using nature-inspired...
With the increasing demand for electrical energy and the challenges related to its production, along with the need to be environmentally friendly to achieve sustainability for... -
Mechanism Design Optimization of a Portable Scanner for Measuring Atmosphere ...
In contrast with other kinds of atmospheric pollutants, light pollution does not present highly-variable patterns in short time periods. Hence, the cost of a monitoring network... -
Optimization of sensor locations for a light pollution monitoring network
Light Pollution is an environmental problem that needs to be retrieved by experimental means. However, to the best of our knowledge, there is no methodology nor a quantitative... -
Improved training of deep convolutional networks via minimum-variance regular...
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and... -
Feature Analysis for Urban-land Change of Morelia City Via the TOC Curve
The feature analysis for feature selection is an important step for defining the inputs of the simulation models for urban growth. The simulation models are valuable tools for... -
Valley Classification using Convolutional Neural Network and a Geomorphons Map
Geomorphological classification serves as a valuable tool for comprehending the origin and evolution of landscapes, as well as for making informed decisions regarding... -
Parameter estimation for empirical and semi-empirical models in a direct etha...
Experimental data from a Direct Ethanol Fuel Cell (DEFC) provides a general perspective about its performance; nevertheless, it does not provide information about the cell's... -
The directed multi-objective estimation distribution algorithm (D-MOEDA)
Improvement Direction Mapping (IDM) methods have been applied as a local search strategy to hybridize global search algorithms. A natural question is whether this concept could... -
“Estimation of peak flow in flood-producing rivers using numerical simulation...
Floods produce enormous human and material losses every year. Evaluating their extent and severity, and especially simulating possible future scenarios can improve the response,... -
Renewable Energy Potential Estimation in Northern Mexico Using GIS
The transition to renewable energy is crucial for addressing pollution and greenhouse gas emissions from activities like electricity generation and transportation. However, the... -
Multivariate Forecasting of Homicide Count for the Metropolitan Zone of Guada...
The Metropolitan Area of Guadalajara (MAG) is the result of an urban conurbation phenomenon involving the capital of the State of Jalisco. It stands as the most politically,... -
Numerical simulation of direct methanol fuel cells using computational fluid ...
Abstract In response to the growing demand of reducing greenhouse gas (GHG) emissions within maritime sector, Onboard Carbon Capture and Storage (OCCS) technologies provide as... -
Constrained optimization of sensor locations for existing light-pollution mon...
The high levels of nocturnal artificial light emissions from urban areas induce adverse effects on the environment and human health. Having adequate monitoring provides... -
The Aiba-Edward kinetics adapted to the macro-homogeneous model for robust PE...
A Proton exchange membrane fuel cell (PEMFC) is a device that efficiently transforms the chemical energy of a fuel into electrical energy, water, and heat. Numerical simulations... -
The Bayesian operating characteristic curve for feature analysis applied to u...
Radio frequency (RF) spectrum sensing is critical for applications requiring precise object and posture detection and classification. This survey aims to provide a focused... -
Graph processing frameworks
This chapter provides a comprehensive overview of Graph Processing Frameworks (GPFs), which are software systems designed to efficiently process large-scale graphs across... -
Self‐adaptive online virtual network migration in network virtualization envi...
In Network Virtualization Environments, the capability of operators to allocate resources in the Substrate Network (SN) to support Virtual Networks (VNs) in an optimal manner is... -
A holistic framework for virtual network migration to enhance embedding ratio...
Network virtualization is a promising technology for overcoming Internet ossification by enabling multiple Virtual Networks (VNs) to coexist on a shared substrate network. One... -
Dash Sylvereye: A WebGL-powered Library for Dashboard-driven Visualization of...
State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not... -
Dash sylvereye: a Python library for dashboard-driven visualization of large ...
State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not... -
Decoding Online Hate in the United States: A BERT-CNN Analysis of 36 Million ...
Since its inception, social media has enabled people worldwide to connect with like-minded individuals and freely express their thoughts and opinions. However, its widespread... -
Whistlerlib: a distributed computing library for exploratory data analysis on...
At least 350k posts are published on X, 510k comments are posted on Facebook, and 66k pictures and videos are shared on Instagram each minute. These large datasets require... -
Enhancing Epidemic Prediction Using Simulated Annealing for Parameter Optimiz...
Understanding and predicting outbreaks of epidemics has become a major focus since COVID-19. Researchers have explored various methods, from basic curve fitting to complex...