Hybrid thermal model for swimming pools based on artificial neural networks for southeast region of Brazil

Authors:
Enock T. Santos;Luis E. ZáRate;Elizabeth M. D. Pereira
Affiliations:
Department of Computer Science, Applied Computational Intelligence Laboratory-LICAP, Pontifical Catholic University of Minas Gerais Av. Dom José Gaspar 500, Coração Eucarıstico ...;Department of Computer Science, Applied Computational Intelligence Laboratory-LICAP, Pontifical Catholic University of Minas Gerais Av. Dom José Gaspar 500, Coração Eucarıstico ...;Centro Universitário-UNA, Campus Raja, Av. Raja Gabáglia, 3.950, bairro Estoril, Belo Horizonte 30494-310, MG, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2013

Citing 7
Cited 0

Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks

Neural Networks
Kolmogorov's theorem and multilayer neural networks

Neural Networks
A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data

Bioinformatics
ENSEMBLE ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF DEW POINT TEMPERATURE

Applied Artificial Intelligence
Estimation of solar radiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey

Expert Systems with Applications: An International Journal
Estimation of global solar radiation using ANN over Turkey

Expert Systems with Applications: An International Journal
Design of neural networks for fast convergence and accuracy: dynamics and control

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	12.05

Visualization

Abstract

Nowadays, the usage of systems based on solar energy have been largely stimulated. The correct designing and efficiency of these systems are highly dependent of the seasonal climatic characteristics of the regions where they will be installed. In this work, we propose a hybrid structure to simulate the thermodynamic behavior of pools, which uses neural computational models to incorporate the climatic information of the regions being analyzed. The neural models have as input variables data of geographic position such as: elevation, latitude and longitude, what permits to delineate the climatic profile of the region being considered. The human activity is another factor that directly influences the thermodynamic behavior of pools and, therefore, is also considered. In this work, changes of volume are estimated in order to track losses due to the human activity.