-
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,... -
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... -
Estimación de datos faltantes de temperatura combinando IDW y una serie trunc...
Este producto no tiene una descripción
-
Optimization of sensor locations for a light pollution monitoring network
Este producto no tiene una descripción
-
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... -
Constrained optimization of sensor locations for existing light-pollution mon...
Este producto no tiene una descripción
-
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... -
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... -
The improvement direction mapping method
Este producto no tiene una descripción
-
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
Este producto no tiene una descripción
-
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... -
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... -
Evaluación comparativa de algoritmos de predicción aplicados al conteo de hom...
Este producto no tiene una descripción
-
A Broyden-based algorithm for multi-objective local-search optimization
Este producto no tiene una descripción
-
Estimación de datos faltantes de temperatura combinando IDW y una serie trunc...
Este producto no tiene una descripción
-
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...
