Time series data modeling and prediction of liquid petroleum gas

Author: 
Prabodh Pradhan, Dr. Bhagirathi Nayak, and Dr. Sunil Kumar Dhal
Abstract: 

Time series modeling and prediction has ultimate meaning to various practical domains. Thus a lot of research works are going on in this subject during several years. Many significant models have been suggested in various literature for improving the precision and effectiveness of time series modeling and prediction. The goal of this article is to present a brief sketch of popular time series prediction models used in practice. We have described here important classes of time series models. We have also discussed about the basic issues related to time series modeling. Here we have collected historical data of Liquid Petroleum Gas (LPG) Domestic consumption from year 2008 to 2014 of every month’s data. We also discussed about various time series models is maintained by giving the experimental prediction results, implemented on time series datasets. While fit a model to a dataset, special care is taken to select and the most ungenerous one. To evaluate prediction precision models fitted to a time series. We have shown the found prediction diagram, which graphically represents the intimacy between the original and prediction observations.

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   Vol. 07, Issue 02, February 2017

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