Abstract
Weather forecasting for an area where the weather and climate changes occurs spontaneously is a challenging task. Weather is non-linear systems because of various components having a grate impact on climate change such as humidity, wind speed, sea level and density of air. A strong forecasting system can play a vital role in different sectors like business, agricultural, tourism, transportation and construction. This paper exhibits the performance of data mining and machine learning techniques using Support Vector Regression (SVR) and Artificial Neural Networks (ANN) for a robust weather prediction purpose. To undertake the experiments 6-years historical weather dataset of rainfall and temperature of Chittagong metropolitan area were collected from Bangladesh Meteorological Department (BMD). The finding from this study is SVR can outperform the ANN in rainfall prediction and ANN can produce the better results than the SVR.
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Rasel, R.I., Sultana, N., Meesad, P. (2018). An Application of Data Mining and Machine Learning for Weather Forecasting. In: Meesad, P., Sodsee, S., Unger, H. (eds) Recent Advances in Information and Communication Technology 2017. IC2IT 2017. Advances in Intelligent Systems and Computing, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-319-60663-7_16
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DOI: https://doi.org/10.1007/978-3-319-60663-7_16
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