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Crop Yield Forecasting for Certain Agriculture Products and Marketing

R. Madhumathi, B.H. Dhivya, R. Manjula, S Siva Bharathi

Abstract


Agriculture is one of the major revenue producing sectors of India and a source of survival. Various seasonal, economic and biological factors influence the crop production but unpredictable changes in these factors lead to a great loss to farmers. These risks can be quantified when appropriate mathematical or statistical methodologies are applied on Data related to soil, weather and past yield are required for this process. With the advent of data mining, crop yield can be predicted by deriving useful insights from these agricultural data that aids farmers to decide on the crop they would like to plant for the forthcoming year leading to maximum profit. In this paper, ARIMA clustering algorithm is used for price forecasting and Multiple Linear Regression algorithm is used for yield prediction. From the experimental results, we have forecasted the yield and price of certain crops.

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References


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