Machine Learning Techniques of Weather Forecasting – A Review
Jitiprova Ghosh *
Assistant Teacher of Physical Science, Aurangabad Balika Vidyalaya (H.S), India.
Amitlal Bhattacharya
Department of Physics, Dukhulal Nibaran Chandra College, Aurangabad, Murshidabad, India.
*Author to whom correspondence should be addressed.
Abstract
Weather is a particular state of the atmosphere that describes the degrees to which it is hot or cold, wet or dry, calm or stormy, clear or cloudy. On earth, most weather phenomena occurs in the lowest layer of the planet’s atmosphere i.e the troposphere. Weather forecasting tools are used in the field of science and technology to forecast atmospheric conditions for a certain place and period. It is a very challenging task for the researchers of this field in this modern era. In this review paper we have tried to estimate the accuracy level of different machine learning method of weather forecasting.
Keywords: Random forest, decision tree, support vector machine, naïve bays, logistic regression, K-nearest neighbors, weather data