Groundnut Crop Yield Prediction Using Machine Learning Techniques

Authors(2) :-Vinita Shah, Prachi Shah

Yield prediction is a very important agricultural problem. Any farmer is interested in knowing how much yield he is about to expect. In the past, yield prediction was performed by considering farmer's experience on particular field and crop. Based on previous data, we can predict crop yield using machine-learning technique. Crop yield prediction is an important area of research, which helps in ensuring food security all around the world. We analyzed result of multiple linear Regression, Regression Tree, K-nearest Neighbor and Artificial Neural Network on Groundnut data of previous 8 years. We have done prediction based on Soil, Environmental and Abiotic attributes. KNN algorithm gives better result compared to other algorithms for Groundnut crop yield prediction.

Authors and Affiliations

Vinita Shah
Assistant Professor, Information Technology, G H Patel College of Engineering and Technology, V V Nagar, Gujarat, India
Prachi Shah
Assistant Professor, Department of Information Technology, BVM Engineering College, V V Nagar, Gujarat, India

Crop analysis; Yield prediction; K-means; K-NN; Multiple Linear regression

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1093-1097
Manuscript Number : CSEIT1835254
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Vinita Shah, Prachi Shah, "Groundnut Crop Yield Prediction Using Machine Learning Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.1093-1097, May-June-2018.
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