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

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.