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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... -
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... -
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... -
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... -
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... -
Improved training of deep convolutional networks via minimum-variance regular...
Fostered by technological and theoretical developments, deep neural networks (DNNs) have achieved great success in many applications, but their training via mini-batch... -
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... -
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,...
