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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: Agricultural analysis for next generation high tech farming in data mining
Authors Name: S.Kavitha , D.Geetha , M.Gomathi , R.Suresh Kumar
Unique Id: IJSDR1610014
Published In: Volume 1 Issue 10, October-2016
Abstract: ABSTRACT: Recent developments in Information Technology for agriculture field have become an interesting research area to predict the crop yield [1]. In today’s world, the amount of information stored has been enormously increasing day by day which is generally in the unstructured form and cannot be used for any processing to extract useful information using mining technique [2]. This paper presents a brief analysis of data mining methods and agriculture techniques, farm types, soil types, prediction using Multiple Linear Regression (MLR) technique for the selected region. This work mainly focuses on analyzing the agricultural analysis of organic farming and inorganic farming, time cultivation of the plant, profit and loss of the data and analyzes the real estate business land in a specific area and comparison of irrigated and unirrigated land. It concentrates organic, inorganic and real estate data sets from which the prediction in agriculture will be achieved. The purpose is to estimate difference in efficiency and prediction between organic and inorganic farming. This work aims at finding suitable data models that achieve a high accuracy and a high generality in terms of yield prediction capabilities.
Keywords: Keywords: Data mining, Agriculture Techniques, Farm Types, Soli Types
Cite Article: "Agricultural analysis for next generation high tech farming in data mining", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 10, page no.82 - 86, October-2016, Available :http://www.ijsdr.org/papers/IJSDR1610014.pdf
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Publication Details: Published Paper ID: IJSDR1610014
Registration ID:160860
Published In: Volume 1 Issue 10, October-2016
DOI (Digital Object Identifier):
Page No: 82 - 86
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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