... individual predictors are arranged to predict solar radiation intensity using historical weather and solar radiation records. Three stacking techniques, namely, feed-forward neural networks, support vector regressors, and k-nearest neighbor regressors, have been examined and compared to combine...

... for the 1 day horizon irradiance forecast are based on artificial neural networks (ANN). With this method, the forecast could be achieved by fast simple algorithms that use only local meteorological measurements [ 5–7 ] and ST feature parameters [ 8 ]. Thus, on one hand, ST models do not suffer from spatial...

... networks, the BFGS neural network was found to perform better by providing 17.39%, 12.63%, and 17.7% improvement in MAE, respectively. Whereas, in terms of MRE, improvements of 16.6%, 12.22%, and 17.00% are found. This justifies the use of BFGS as the NN algorithm for model construction. The BFGS...

...-mining algorithms are used to build models with turbine parameters of interest as inputs, and the vibrations of drive train and tower as outputs. The performance of each model is thoroughly evaluated based on metrics widely used in the wind industry. The neural network algorithm outperforms other...

...Moncef Krarti An overview of commonly used methodologies based on the artificial intelligence approach is provided with a special emphasis on neural networks, fuzzy logic, and genetic algorithms. A description of selected applications to building energy systems of AI approaches is outlined...