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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... -
Estimación de datos faltantes de temperatura combinando IDW y una serie trunc...
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Optimization of sensor locations for a light pollution monitoring network
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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...
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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
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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... -
Comparison of Parallel Versions of SA and GA for Optimizing the Performance o...
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Industrial and Robotic Systems: LASIRS 2019
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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
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The improvement direction mapping method
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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
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Robust parameter estimation of a PEMFC via optimization based on probabilisti...
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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...