Chinnathambi, K. and Kandimalla, Rajyalakshmi and Rayala, Srihari (2025) Predicting Agricultural Success with Machine Learning. In: Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part II.
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Abstract
This report applies the KNN algorithm, a simple yet effective machine learning method, to predict agricultural success. Through historical agricultural data, weather information, soil conditions, and other related data, the KNN model forecasts crop yields with high precision. This forecast will serv
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 20:20 |
| Last Modified: | 16 Apr 2026 15:50 |
| URI: | http://eprints.eai.eu/id/eprint/60255 |
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