Using Deep Learning Techniques to Predict Wind Speed

Abstract

Author(s): Waleed Saleh Hamed, Dr. Karim Q. Hussein

As a result of the rise in ecological pollution, the decrease in gas gets, and also the increase in power consumption against the rise in the population, researchers and scientists have motivated to concentrate their research on tidy as well as environmentally pleasant eco-friendly energy 'sources. Wind energy is a 'renewable resource that is cost-free from gas discharges during 'operation and does not need fuel costs. For that reason, wind power has actually drawn in those curious about producing in this work, the design was developed and also carried out based upon deep knowing methods for LSTM formulas, to execute several research studies to integrate 'this energy into the electrical power grid. SVR, KNN 'Regression on Kaggle World dataset.' Models were examined utilizing analytical measures mean outright mistake (MAE) origin indicate square mistake, (RMSE). The version helps to enhance the forecast and reduce the issue of arbitrary modifications in wind rate.