Crop Prediction Analysis in North western Zone of Tamilnadu using Artificial Bee Colony with Weighted based Fuzzy Clustering
P.Surya1, I.Laurence Aroquiaraj2
1P.Surya*, PhD Research Scholar, Department of Computer Science, Periyar University, Salem, Tamil Nadu, India.
2Dr. I. Laurence Aroquiaraj, Assitant Professor, Department of Computer Science, Periyar University, Salem, Tamil Nadu, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 3259-3274 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8838088619/2019©BEIESP | DOI: 10.35940/ijeat.F8838.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Agriculture is most important part for living people. Crop prediction analysis is more useful analysis to choose the particular crop for cultivation in particular season. In this paper, a hybridization technique that is Artificial Bee Colony with weighted based Fuzzy Clustering algorithm was proposed to predict a district which produces a most high yield in the north western zone of Tamil Nadu in that particular district. North western zone of Tamil Nadu consist four districts such as Dharmapuri, Krishnagiri, Namakkal and Salem. In this research work the proposed algorithm shows that the district in the north western zone of Tamil Nadu which yields high production of particular crop for that particular season. In north western zone of Tamil Nadu, Crop prediction analysis consider as high yield area, moderate yield area and low yield area as district wise. The Experimental result shows that hybridized artificial bee colony with weighted based fuzzy clustering algorithm yields better performance than other clustering algorithm like k-means and k-medoids with high accuracy.
Keywords: Data mining, Clustering, Fuzzy clustering, Artificial Bee Colony, Agriculture, Crop prediction analysis.