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Comparative Study on Bio-inspired Approach for Soil Classification

by K. Sumangala, G. Nithya
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 4
Year of Publication: 2012
Authors: K. Sumangala, G. Nithya
10.5120/4678-6799

K. Sumangala, G. Nithya . Comparative Study on Bio-inspired Approach for Soil Classification. International Journal of Computer Applications. 38, 4 ( January 2012), 32-37. DOI=10.5120/4678-6799

@article{ 10.5120/4678-6799,
author = { K. Sumangala, G. Nithya },
title = { Comparative Study on Bio-inspired Approach for Soil Classification },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 4 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number4/4678-6799/ },
doi = { 10.5120/4678-6799 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:41.927043+05:30
%A K. Sumangala
%A G. Nithya
%T Comparative Study on Bio-inspired Approach for Soil Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 4
%P 32-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ant miner is a data mining algorithm based on Ant Colony Optimization. Ant miner algorithms are mainly for discovery rule for optimization. Ant miner+ algorithm uses MAX-MIN ant system for discover rules in the database. Soil classification deals with the systematic categorization of soils based on distinguished characteristics as well as criteria. In this paper, Ant miner and Ant miner+ algorithm were applied to both training and soil dataset to obtain classification rules and found that Ant miner+ performs better than Ant miner.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ant Colony Optimization Ant miner Ant miner+

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