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Crop Production Estimator


Mitunkumar Balar , charotar university of science and technology; Ronakkumar Patel, charotar university of science and technology


Crop Prediction, Neural Network, K-means clustering


India is an agricultural country and agriculture plays important role in GDP of India. Due to lack of an irrigation system, the farmer mostly relies on rain. The uncertainty of rain and land per hector plays important role in a production of the crop. There are other criteria as well which affect the crop prediction like soil PH, Nitrogen, Soil Depth, temperature etc. In this paper Machine Learning approach used to predict the production of the particular crop in a particular district using rain and available land. The Neural Network is used to train the model. This will help the farmer to predict how much production he should expect and whether to go for that crop in that year. The model is evaluated using RMSE, MAE and compared with K-means clustering algorithm. Results show that the NN is giving good result compare to K-means.

Other Details

Paper ID: IJSRDV6I110136
Published in: Volume : 6, Issue : 11
Publication Date: 01/11/2019
Page(s): 438-441

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