πŸ“ž +91-7667918914 | βœ‰οΈ ijireeice@gmail.com
International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering
International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2321-2004ISSN Print 2321-5526Since 2013
IJIREEICE meets the suggestive parameters outlined in the latest University Grants Commission (UGC) for peer-reviewed journals, ensuring high standards of research integrity, publication ethics, and academic excellence.
← Back to VOLUME 8, ISSUE 4, APRIL 2020

Time Series Prediction of Crop Yield based on Time Alignment using Machine Learning

Manjula H.N, Namratha S, Shiva Prasad K

πŸ‘ 1 viewπŸ“₯ 0 downloads
Share: 𝕏 f in ✈ βœ‰
Abstract: Food production in India is largely dependent on cereal crops including rice, wheat and various pulses.The sustainability and productivity of crops growing areas is dependent on suitable climatic conditions.Variability in seasonal climate conditions can have detrimental effects, with incidents of drought reducing production. Developing better techniques to predict crop productivity in different climatic conditions can assist farmers in better decision making in terms of agronomy and crop choice. Machine learning techniques can be used to improve prediction of crop yield under different climatic scenarios. This paper presents the review on use of such machine learning techniques for cropping areas.

Keywords: Machine Learning, Linear Regression, Random Forest Regression, Prediction.

How to Cite:

[1] Manjula H.N, Namratha S, Shiva Prasad K, β€œTime Series Prediction of Crop Yield based on Time Alignment using Machine Learning,” International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2020.8416

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.