Diseño de un algoritmo utilizando Machine Learning para la predicción de la radiación solar en el sector de Lasso. - Lalaleo Achachi, Diego Fernando (2021)
The design of the algorithm for the prediction of solar radiation using Machine Learning techniques was developed by applying the keras and Tenson Flow libraries for the creation of the LSTM sequential model neural network that selected previous data and predicted a later week, was recorded with a meteorological station the measurement of the climate variables in intervals of every minute to export the measurement file in .CSV format, the data processing was coded in Google Colab so that the information resources are carried out by the server, the programming language is Python, the results obtained are values of solar radiation in the range from 6:00 a.m. to 6:00 p.m., the sequence of hours with time is relevant, if a value was null or the order of the data is altered, the results are different from the real ones because time series are applied to the forecast data and the result is the forecast for each hour of the following seven continuous days.