Prediction of Weather Forecasting with Long Short-Term Memory using Deep Learning
S. Karthika, T. Priyanka, J. Indirapriyadharshini, S Sadesh, G Rajeshkumar, P. Rajesh Kanna
Abstract
Weather forecasting has a greater effect on human life, recently this filed has gained a significant research attention. The existing numerical weather prediction models are very complex to solve. Therefore, the primary goal of this research work is to create a novel and lightweight weather forecasting model. Here, the time series data have been used from Kaggle website. The obtained dataset is then processed with the help of deep learning techniques. The Long Short-Term Memory (LSTM) algorithm is used to produce better result with more accuracy when compared with other deep learning methodologies. Therefore, from the results it is evident that the proposed model can be used to predict the weather conditions with greater accuracy and assist farmers and others who depend on weather.