Pavitra Kadiyala, Vallabhaneni Sri Harsha Sai·October 2020·pp. 01-03
Agriculture is a very important aspect of one’s life. One essential thing for a living being is food. Crop production plays a major role in the amount of food available. Crop production prediction is very important as this will give the farmers and other human beings a rough idea of the prices of food as well as the amount of available food. Machine Learning and Artificial Intelligence help us predicting a few aspects which are difficult for humans to predict. With the help of this domain, we can predict the amount of production of crops in a particular area given the amount of rainfall and the area of land present. This research aims to predict the amount of crop production based on multiple factors such as rainfall, area, location, and type of crop.
Pavitra Kadiyala
School of Computer Science & Engineering, VIT, Vellore, India - **Vallabhaneni Sri Harsha Sai**, School of Computer Science & Engineering, VIT, Vellore, India
**[1] Dataset: District-wise, season-wise crop production statistics from 1997 and District-wise, rainfall statistics. [2] Priya, P., Muthaiah, U., Balamurugan, M. (n.d.). Predicting yield of the crop using machine learning algorithm. International Journal of Engineering Sceinces Research Technology, 7(4),1-7 [3] Dr. V. Latha Jothi, Neelambigai A, Nithish Sabari S, Santhosh K, 2020, Crop Yield Prediction using KNN Model, International Journal of Engineering research Technology (IJERT). [4] RTICCT – 2020 (Volume 8 – Issue 12), N. Gandhi, L. J. Armstrong, O. Petkar and A. K. Tripathy, ”Rice crop yield prediction in India using support vector machines,” 2016 13th International Joint Conference on Computer Science and Software En- gineering (JCSSE), Khon Kaen, 2016, pp. 1-5, doi: 10.1109/JCSSE.2016.7748856. [5] R. Kumar, M. P. Singh, P. Kumar and J. P. Singh, ”Crop Selection Method to maximize crop yield rate using machine learning technique,” 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), Chennai, 2015, pp. 138-145, doi: 10.1109/ICSTM.2015.7225403. [6] Thomas van Klompenburg, Ayalew Kassahun, Cagatay Catal, Crop yield prediction using machine learning: A systematic literature review, Computers and Electronics in Agriculture, Volume 177, 2020, 105709, ISSN 0168- 1699, [7] Champaneri, Mayank Chachpara, Darpan Chandvidkar, Chaitanya Rathod, Mansing. (2020). Crop yield prediction using machine learning. Inter- national Journal of Science and Research (IJSR). 9. 2.**
Pavitra Kadiyala, Vallabhaneni Sri Harsha Sai "Crop Production Prediction using Machine Learning" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 1, October 2020, pp.01-03 URL: www.ijltemas.in/DigitalLibrary/Vol.10Issue1/01-03.pdf
