Abstract
For attaining spatial time-series data in past one decade many of the attempts have been implemented on data sets to perform various processes for mining and classifying prediction rules. A novel approach is proposed in this paper for mining time-series data on cloud model we used wallmart data set. This process is performed over numerical characteristic oriented datasets. The process includes theory of cloud model with expectation, entropy and hyper-entropy characteristics. Then data is attained using backward cloud model by implementing on Libvirt. Using curve fitting process numerical characteristics are predicted. The proposed model is considerably feasible and is applicable in performing forecasting over cloud.
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Narasimha Rao, S., Ram Kumar, P. (2020). Time Series Data Mining in Cloud Model. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-24322-7_31
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DOI: https://doi.org/10.1007/978-3-030-24322-7_31
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