Analysis of Crop Yield Prediction using Fuzzy Clustering techniques

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Published: Dec 21, 2020
DOI: https://doi.org/10.26483/ijarcs.v11i6.6671
Keywords:
Data Mining, Fuzzy Clustering, Agriculture, Different Techniques

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POORNIMA K A
"Bharathiar university"
Dr.DHEEPA G
Bharathiar University

Abstract

Nowadays the most important field in the real world is agriculture and it is the main occupation and backbone of our Indian economy. Agriculture data analysis is one of the latest drift research fields in data mining. Crop yield prediction is vital as it can support decision makers in agriculture zone. Data mining have modern techniques and algorithms for finding best yield prediction. This paper presents a brief comparative study on different views that deals with various performances used to figure out the different crop yield with less error rate. Fuzzy C-Means(FCM), Fuzzy logic (FL), Adaptive Neuro Fuzzy Inference System(ANFIS),Multiple Linear Regression(MLR), Linear Discriminant Analysis (LDA) are used to survey out high accuracy and less error rate prediction capabilities.

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Article Details

Issue
Vol. 11 No. 6 (2020): November - December 2020
Section
Articles

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Author Biographies

POORNIMA K A, "Bharathiar university"

Assistant Professor,

Department of Computer Science

Gobi Arts and Science College (Autonomous)

Gobichettipalayam

Dr.DHEEPA G, Bharathiar University

Assistant Professor,

Department of Computer Science

P.K.R.Arts College for Women (Autonomous) 

Gobichettipalayam

References

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