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Classification of agricultural productivity index of Cauvery delta zone using artificial neural network

DOI: 10.18805/asd.v0iOF.4436    | Article Id: D-4385 | Page : 261-266
Citation :- Classification of agricultural productivity index of Cauvery deltazone using artificial neural network .Agricultural Science Digest.2016.(36):261-266

G. Manimannan*1, C. Arulkumar2 and R. Lakshmi Priya3

manimannang@gmail.com
Address :

Department of Statistics, DRBCCC Hindu College, Pattabiram, Chennai-60 072, Tamilnadu, India.

Submitted Date : 3-03-2016
Accepted Date : 1-10-2016

Abstract

In this study a novel trial was made to classify the Agriculture Productivity Index (API) for the major crops of Cauvery Delta Zone (CDZ) using neural network and statistical methods. At present the CDZ includes, Tanjavur, Tiruvarur, Nagapattinam, Tiruchirapalli, Pudukottai and Ariyalur districts. The crops grown in the Cauvery delta zone were categorized into four major groups such as, cereals, pulses, oilseeds and cash crops. The data for the period of 2003 to 2012 were collected from the Department of Economics and Statistics, Chennai, Tamilnadu. Enyedi’s method was adopted to calculate the API and based on the index the regions were classified by neural network method using Learning Vector Quantization (LVQ). The classification was cross validated statistically, using Multivariate Discriminant Analysis (MDA). The classification results achieved 83% in LVQ and 97% MDA respectively in the entire period of study. The results are obtained as Greater Productivity Regions (GPR), Moderate Productivity Regions (MPR) and Lesser Productivity Regions (LPR)  and are plotted in Tamil Nadu spatial map with different colours. 

Keywords

Agriculture productivity index Cauvery delta zone Learning vector quantization Multivariate discriminant analysis Novel classification trial Spatial Pattern.

References

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