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Reseach Article

Application of Cluster Analysis in Agriculture-A Review Article

by Mamta Tiwari, Dr. Bharat Misra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 36 - Number 4
Year of Publication: 2011
Authors: Mamta Tiwari, Dr. Bharat Misra
10.5120/4478-6298

Mamta Tiwari, Dr. Bharat Misra . Application of Cluster Analysis in Agriculture-A Review Article. International Journal of Computer Applications. 36, 4 ( December 2011), 43-47. DOI=10.5120/4478-6298

@article{ 10.5120/4478-6298,
author = { Mamta Tiwari, Dr. Bharat Misra },
title = { Application of Cluster Analysis in Agriculture-A Review Article },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 36 },
number = { 4 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume36/number4/4478-6298/ },
doi = { 10.5120/4478-6298 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:22:19.561409+05:30
%A Mamta Tiwari
%A Dr. Bharat Misra
%T Application of Cluster Analysis in Agriculture-A Review Article
%J International Journal of Computer Applications
%@ 0975-8887
%V 36
%N 4
%P 43-47
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we humbly present a review of some applications of cluster analysis in the field of agriculture and allied sciences. A few applications among them, which have been discussed here includes hierarchical agglomerative clustering approach, fuzzy clustering, hierarchical divisive clustering and Kohonen self-organizing feature maps along with an application of each of these techniques in the field of agriculture is also presented. Data mining in agriculture is a relatively new research field and the use of cluster analysis has almost been just begun in this area. This is our strong belief that effective techniques can be carved out for solving different agricultural problems of various complexities by intelligent use of data mining and its tools such as cluster analysis.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Agriculture Data mining Fuzzy clustering Hierarchical agglomerative clustering Hierarchical divisive clustering Kohonen self-organizing feature maps