Statistical Model and Neural Networks based Weather Forecasting

Weather conditions change endlessly and it is very essential for people to know these changes and predict the weather in order to decide there day to day task. A person may confuse prediction with the forecast, the main difference is forecast is statistical and scientific and free from intuitions whereas prediction is subjective in nature. Traditionally atmosphere is modeled as fluid. And future weather is predicted using fluid dynamics and thermodynamics, but since machine learning techniques are more robust to perturbations, so in this paper we have decided to explore its application to weather forecasting to generate more accurate result. This paper discusses various methods used in deep neural networks and statistical models to find the most appropriate method for forecasting weather based on a very minimalistic weather related data set to reduce data collection overheads. It also outlines an IOT based pipeline to collect data in real time to update existing models and forecast accordingly. Citation: A. Velayudham, M. S. Krishna Priya. "Statistical Model and Neural Networks based Weather Forecasting." Global Research and Development Journal For Engineering 4.10 (2019): 6 - 11.