review and classification of electric load forecasting (lf) techniques based on artificial neuralnetworks (ann) is presented. a basic anns architectures used in lf reviewed. a wide range of annoriented applications for forecasting are given in the literature. these are classified into five groups:(1) anns in short-term lf, (2) anns in mid-term lf, (3) anns in long-term lf, (4) hybrid anns inlf,...

Urban road intersection bottleneck has become an important factor in causing traffic delay and restricting efficiency. It is essential to explore the prediction of operating performance at intersections real-time formulate corresponding strategies alleviate delay. However, because sophisticated condition, it difficult capture Spatio-temporal features by traditional data methods. The development...

Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...