An Application of Fuzzy C-Means Based Clustering Technique in Smart Farming

DOI

10.2991/isrme-15.2015.150How to use a DOI?

Keywords

Precision farming; Fuzzy c-means clustering; apparent electrical conductivity

Abstract

Customised farming has seen ever increasing interest of next level farming practices across the globe by the modern agronomist of the age. Customized Management practices (CMP) make use of creating management zones (MZs’), leading to precision farming through application of variable rate technology for soil inputs. In this paper site-specific Apparent Electrical conductivity (ECa) and crop yield information have been used to study the spatial distribution and variability of the land. Matlab 8.5 version was used to implement Fuzzy c-means clustering in order to cluster the data and various performance indices such as NCE, FPI and their ifference were calculated to determine the clustering performance. Both the clusters (ECa and crop yield) were mapped and good amount of overlap was observed indicating the relationship between ECa and crop yield.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhuo Tian
AU  - Baicheng Li
PY  - 2015/04
DA  - 2015/04
TI  - An Application of Fuzzy C-Means Based Clustering Technique in Smart Farming
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 744
EP  - 747
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.150
DO  - 10.2991/isrme-15.2015.150
ID  - Tian2015/04
ER  -