A MODEL FOR THE ESTIMATION OF THE VOLUME OF CROPS PRODUCED
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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Abstract
Data mining to analyse agricultural output is a rapidly expanding study area. The inability to reliably forecast harvests is a serious problem in the agricultural sector. Every grower has to know what kind of yield they may anticipate. In the past, productivity estimates relied heavily on farmers' prior knowledge of a certain area and crop. Given the available data, it's clear that the yield forecast needs serious attention. In this case, data mining is the most effective method. Agriculture evaluates several data mining tools to foretell future agricultural yields. This study implements a technique for forecasting agricultural production using past data. Association rule mining may be used to agricultural data to achieve this. To better anticipate agricultural output in the future, we want to develop a model for doing so. To forecast agricultural output for a certain area in a Tamil Nadu, India district, we use an association rules-based data mining strategy in this investigation. The experimental data shows that the proposed strategy is useful for predicting agricultural yields.
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Keywords
Yield Prediction, Data Mining, Agriculture.
