SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS

In any production environment, processing is centered on the manufacture of products. It is important to get adequate volumes of orders for those products. However, merely getting orders is not enough for the long-term sustainability of multinationals. They need to know the demand for their products...

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Main Authors: Rashmi Ranjan Dhal, B.V.A.N.S.S. Prabhakar Rao
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2014-10-01
Series:ICTACT Journal on Soft Computing
Subjects:
Online Access:http://ictactjournals.in/paper/IJSC_Splissue_Oct2014_Paper_6_869_874.pdf
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author Rashmi Ranjan Dhal
B.V.A.N.S.S. Prabhakar Rao
author_facet Rashmi Ranjan Dhal
B.V.A.N.S.S. Prabhakar Rao
author_sort Rashmi Ranjan Dhal
collection DOAJ
description In any production environment, processing is centered on the manufacture of products. It is important to get adequate volumes of orders for those products. However, merely getting orders is not enough for the long-term sustainability of multinationals. They need to know the demand for their products well in advance in order to compete and win in a highly competitive market. To assess the demand of a product we need to track its order behavior and predict the future response of customers depending on the present dataset as well as historical dataset. In this paper we propose a systematic, time-series based scheme to perform this task using the Hadoop framework and Holt-Winter prediction function in the R environment to show the sales forecast for forthcoming years.
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spelling doaj.art-02c51906432845b08bd8efa58c7f57702022-12-22T03:56:54ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562014-10-0151869874SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSISRashmi Ranjan Dhal0B.V.A.N.S.S. Prabhakar Rao1School of Computing Science and Engineering, VIT University, Chennai, IndiaSchool of Computing Science and Engineering, VIT University, Chennai, IndiaIn any production environment, processing is centered on the manufacture of products. It is important to get adequate volumes of orders for those products. However, merely getting orders is not enough for the long-term sustainability of multinationals. They need to know the demand for their products well in advance in order to compete and win in a highly competitive market. To assess the demand of a product we need to track its order behavior and predict the future response of customers depending on the present dataset as well as historical dataset. In this paper we propose a systematic, time-series based scheme to perform this task using the Hadoop framework and Holt-Winter prediction function in the R environment to show the sales forecast for forthcoming years.http://ictactjournals.in/paper/IJSC_Splissue_Oct2014_Paper_6_869_874.pdfTime Series AnalysisSales PredictionHadoop Distributed File SystemHolt-Winters FunctionSeasonal and Level Variant
spellingShingle Rashmi Ranjan Dhal
B.V.A.N.S.S. Prabhakar Rao
SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
ICTACT Journal on Soft Computing
Time Series Analysis
Sales Prediction
Hadoop Distributed File System
Holt-Winters Function
Seasonal and Level Variant
title SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
title_full SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
title_fullStr SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
title_full_unstemmed SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
title_short SHRINKING THE UNCERTAINTY IN ONLINE SALES PREDICTION WITH TIME SERIES ANALYSIS
title_sort shrinking the uncertainty in online sales prediction with time series analysis
topic Time Series Analysis
Sales Prediction
Hadoop Distributed File System
Holt-Winters Function
Seasonal and Level Variant
url http://ictactjournals.in/paper/IJSC_Splissue_Oct2014_Paper_6_869_874.pdf
work_keys_str_mv AT rashmiranjandhal shrinkingtheuncertaintyinonlinesalespredictionwithtimeseriesanalysis
AT bvanssprabhakarrao shrinkingtheuncertaintyinonlinesalespredictionwithtimeseriesanalysis