Path: Top -> Journal -> Jurnal ITB -> 2017 -> Vol 11, No 2

A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction

Journal from gdlhub / 2017-11-06 11:05:31
Oleh : Neelam Mishra, Hemant Kumar Soni, Sanjiv Sharma, A.K. Upadhyay, ITB
Dibuat : 2017-11-06, dengan 1 file

Keyword : data mining; intelligent forecasting model; neural network; rainfall forecasting; rainfall and runoff patterns; statistical techniques; time series data mining; weather prediction
Url : http://journals.itb.ac.id/index.php/jictra/article/view/2604
Sumber pengambilan dokumen : WEB

Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting. Various techniques are available for prediction and forecasting on the basis of time series data. Presently, the use of data mining techniques for this purpose is increasing day by day. In the present study, a comprehensive survey of data mining approaches and statistical techniques for rainfall prediction on time series data was conducted. A detailed comparison of different relevant techniques was also conducted and some plausible solutions are suggested for efficient time series data mining techniques for future algorithms

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ID Publishergdlhub
OrganisasiITB
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KotaJambi
DaerahJambi
NegaraIndonesia
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