Soil data clustering by using K-means and fuzzy K-means algorithm

Elma Hot; Vesna Popović–Bugarin

doi:10.1109/telfor.2015.7377608

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Soil data clustering by using K-means and fuzzy K-means algorithm

Elma Hot Vesna Popović–Bugarin

Year: 2015 Pages: 890-893

DOI: 10.1109/telfor.2015.7377608

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Abstract

A problem of soil clustering and spatial representation of the obtained results, based on in-situ measurements of physical and chemical characteristics of soil, is analysed in the paper. K-means and fuzzy K-means algorithms are adapted for the soil data clustering. Database of soil samples sampled in Montenegro is used for comparative analysis of the used algorithm. Classified soil data are presented on static Google map.

Keywords:

Cluster analysis Fuzzy clustering Data mining Computer science Montenegro Fuzzy logic Algorithm Soil science Pattern recognition (psychology) Artificial intelligence Environmental science Geography

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Topics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Soil Geostatistics and Mapping

Physical Sciences → Environmental Science → Environmental Engineering

Soil data clustering by using K-means and fuzzy K-means algorithm

Abstract

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Citation History

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