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Analysis of Soil Behaviour and Prediction of Crop Yield Using Data Mining Approach

机译:数据挖掘方法分析土壤行为并预测作物产量

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Yield prediction is very popular among farmers these days, which particularly contributes to the proper selection of crops for sowing. This makes the problem of predicting the yielding of crops an interesting challenge. Earlier yield prediction was performed by considering the farmer's experience on a particular field and crop. This work presents a system, which uses data mining techniques in order to predict the category of the analyzed soil datasets. The category, thus predicted will indicate the yielding of crops. The problem of predicting the crop yield is formalized as a classification rule, where Naive Bayes and K-Nearest Neighbor methods are used.
机译:如今,单产预测在农民中非常流行,这尤其有助于正确选择播种的农作物。这使得预测农作物产量的问题成为一个有趣的挑战。早期产量预测是通过考虑农民在特定田地和农作物上的经验进行的。这项工作提出了一个系统,该系统使用数据挖掘技术来预测所分析土壤数据集的类别。因此预测的类别将指示农作物的产量。预测作物产量的问题已被正式定义为分类规则,其中使用了朴素贝叶斯(Naive Bayes)和近邻K(K-Nearest Neighbor)方法。

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