Predicting Wind Turbine Performance Using Machine Learning Techniques

Wind energy is a rapidly growing field, and the ability to accurately predict wind turbine performance essential for optimizing production. Machine learning technology has been successfully applied using various models such as neural networks, decision trees, support vector machines. However, traditional machine networks require significant amount of time train optimize, their can be affected by overfitting underfitting. To address these challenges, proposed backpropagation algorithm introduced network model. The methodology used in real-world scenarios optimize production, contributing transition towards sustainable clean sources.