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Title	Role Of Machine Learning In Weather Related Event Predictions For A Smart City
ID_Doc	47024
Authors	Umer M.A.; Jilani M.T.; Junejo K.N.; Naz S.A.; D’Silva C.W.
Year	2021
Published	Studies in Computational Intelligence, 971
DOI	http://dx.doi.org/10.1007/978-3-030-72065-0_4
Abstract	Weather related event prediction is always a fascinating problem for scientists due to its importance in different sectors of life. This chapter has used machine learning algorithms to predict events like rainfall, thunderstorm, and fog in a large metropolitan city. The study proposed here has particularly focused on the long-term event predictions which is currently missing in the state of the artwork. Different machine learning algorithms mainly Random Forest, Gradient Boosting Classifier, Logistic Regression, and others were used to learn the model. Five years of meteorological data was used for this purpose. Different algorithms showed accuracy more than 90%, among which Random Forest outperformed the other algorithms by achieving the highest accuracy. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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