A Powerful GRU-Based Deep Learning Weatherman to Predict Temperature for Visakhapatnam

In the contemporary landscape of weather forecasting, a tremendous surge in the utilization of deep learning techniques had been witnessed. This is mainly because deep learning models have the potential to capture complex and non-linear relationships between meteorological variables, making them suitable for predicting weather patterns accurately. One class of such models are the GRUs (Gated Recurrent Units), which have proved high effectiveness in predicting temperature with great precision. This study explores the utilization of the GRU model for predicting the temperature patterns in Visakhapatnam, a coastal city. To train the GRU model, we employed historical temperature data and meteorological variables as input features so that it learns the patterns and dependencies existing in the data. The evaluation encompassed a variety of performance metrics, including the error of the absolute mean, the square of the error of the mean and its root, coefficient of determination, the error of the absolute percentage of the mean, the explained score of variances, as well as training and test loss. The experimental outcomes underscore the high accuracy as well as the efficiency of the GRU-based artificial neural network model in predicting temperature for Visakhapatnam. The GRU model produced a mean absolute error of 0.045 for maximum temperature and 0.049 for minimum temperature, respectively. In addition, the root mean squared error obtained as 0.0653 and 0.667 for the two categories of temperatures in respective manner. These findings highlight the immense promise of employing deep learning methodologies in weather prediction, with a notable emphasis on the effectiveness demonstrated by the GRU model. The research underscores the importance of harnessing sophisticated deep learning models for weather forecasting, offering the potential for enhanced precision and reliability in temperature predictions. Our results indicate that the GRU model stands out as a proficient and reliable tool for forecasting temperatures in Visakhapatnam, and potentially, in other geographical regions too.