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The house is burning: assessment of habitat loss due to wildfires in Central ...
Fire suppression and climate change have increased the frequency and severity of wildfires, but the responses of many organisms to wildfire are still largely unknown. In this... -
Constrained optimization of sensor locations for existing light-pollution mon...
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Toxicological and Carcinogenic Risk from Fluoride and Arsenic in Drinking Wat...
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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
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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
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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...
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A Broyden-based algorithm for multi-objective local-search optimization
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Estimación de datos faltantes de temperatura combinando IDW y una serie trunc...
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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... -
Consumo de agua industrial en el Bajío: un análisis por Zona Metropolitana, 2...
El análisis de las zonas metropolitanas en diversos indicadores de desempeño económico y de sustentabilidad, como la productividad y el consumo de agua a nivel industrial, es un... -
Mechanism Design Optimization of a Portable Scanner for Measuring Atmosphere ...
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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...
