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Title	Car Park Occupancy Rates Forecasting Based On Cluster Analysis And Knn In Smart Cities
ID_Doc	13391
Authors	Muntean M.V.
Year	2019
Published	Proceedings of the 11th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2019
DOI	http://dx.doi.org/10.1109/ECAI46879.2019.9042098
Abstract	In car park occupancy problem, large amounts of data are collected from sensors and stored in databases. In order to discover useful information from such data, data mining techniques are applied. In this paper I propose to find alternative solutions for Birmingham car park occupancy issue. Our approach consist in clustering first the dataset in order to obtain relevant periods of time within a day and then forecast data within these clusters. Our experiments show that splitting data into six clusters and predict car park occupancy with k-Nearest Neighbor technique lead to the highest forecast rates. © 2019 IEEE.
Author Keywords	Clustering; Forecasting; K-means; KNN; Smart city

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