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Reseach Article

Decision Support System for Farmers using Business Intelligence

Published on February 2013 by Ronak Thakker, Prathmesh Raut, Vatsal Mehta, Gresha Bhatia
International Conference on Recent Trends in Information Technology and Computer Science 2012
Foundation of Computer Science USA
ICRTITCS2012 - Number 11
February 2013
Authors: Ronak Thakker, Prathmesh Raut, Vatsal Mehta, Gresha Bhatia
e73ce712-e915-4847-a4ba-2ee0029bc160

Ronak Thakker, Prathmesh Raut, Vatsal Mehta, Gresha Bhatia . Decision Support System for Farmers using Business Intelligence. International Conference on Recent Trends in Information Technology and Computer Science 2012. ICRTITCS2012, 11 (February 2013), 1-4.

@article{
author = { Ronak Thakker, Prathmesh Raut, Vatsal Mehta, Gresha Bhatia },
title = { Decision Support System for Farmers using Business Intelligence },
journal = { International Conference on Recent Trends in Information Technology and Computer Science 2012 },
issue_date = { February 2013 },
volume = { ICRTITCS2012 },
number = { 11 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/icrtitcs2012/number11/10409-1303/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Information Technology and Computer Science 2012
%A Ronak Thakker
%A Prathmesh Raut
%A Vatsal Mehta
%A Gresha Bhatia
%T Decision Support System for Farmers using Business Intelligence
%J International Conference on Recent Trends in Information Technology and Computer Science 2012
%@ 0975-8887
%V ICRTITCS2012
%N 11
%P 1-4
%D 2013
%I International Journal of Computer Applications
Abstract

Farmers in India work extremely hard in the farms but still their profit margins are comparatively low. The farmers have very little knowledge about the conditions that cause fluctuations in price of the crop. These fluctuations in the price are due to various factors like irregular rainfall, change in demand-supply, and import-export policies of the government. We, therefore, implemented Holt-winter's Forecasting Model and have incorporated the effects caused by factors such as Rainfall, Exports-Imports & Productivity into the model. This model examines some sample data and based on this data, forecasts the future trend and fluctuations in crop price. This model can help the farmers by providing prediction of price of the crops and thus, to extend the profit margins.

References
  1. Shouhua Yu and Jingying Ou, "Forecasting Model of Agricultural Products Prices in Wholesale Markets Based on Combined BP Neural Network -Time Series Model", in 2009 International Conference on Information Management, Innovation Management and Industrial Engineering.
  2. Tejas Ghadiyali, Kalpesh Lad and Bankim Patel, "Agriculture Intelligence: An Emerging Technology for Farmer Community", in 2011 Second International Conference on Emerging Applications of Information Technology.
  3. Li Junfeng and Niu Jiangao , "Analysis on Demands for Agricultural Science and Technology Based on Bayesian Network", in 2011 Fourth International Conference on Business Intelligence and Financial Engineering.
  4. Deping Zhan and Bingyu Cao "Market Failure and Supply Model of Chinese Agricultural Insurance", in 2010 Third International Conference on Business Intelligence and Financial Engineering. 7. 2 Links visited
  5. For rainfall data in Pune, referred monsoon reports of years 2008 to 2011 from http://www. imdpune. gov. in/
  6. For actual Spot Prices: http://www. ncdex. com/MarketData/SpotPrice. aspx
  7. For Exports data: http://www. sopa. org/st16. htm
  8. For selection of Holt Winter's Method: http://home. ubalt. edu/ntsbarsh/Businessstat/otherapplets/PolynoReg. htm
  9. For comparison of forecasting methodologies and Selection of Holt Winters Method http://www. decisioncraft. com/dmdirect/forecastingtechnique. htm
Index Terms

Computer Science
Information Sciences

Keywords

Agricultural Products Wholesale Prices Forecast Holt-winters' Forecasting Model