Improve Villupuram district yield cultivation using recommendation system by machine learning

Praveena, R. and Kalpana, Y. (2022) Improve Villupuram district yield cultivation using recommendation system by machine learning. In: 4TH INTERNATIONAL CONFERENCE ON MATERIALS ENGINEERING & SCIENCE: Insight on the Current Research in Materials Engineering and Science, 6–7 October 2021, Duhok, Kurdistan Region, Iraq.

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Abstract

Villupuram is one of the most rural cities in Tamil Nadu. In this research, we will look at the climatic conditions suitable for future cropping. Recommendations for future crops. This research will look at the most important crops we have taken and the seasonal reference for each crop. Here we will look at each crop's seasonal concern and the benefits and effects of short-term and long-term yields. For this study, we will take the agricultural data in Villupuram district as an example for two years, 1990 to 1991 and 2019 to 2020, and how agricultural production took place in 1990. We will also see how agriculture production is going on at present. IMD based on weather and climate future prediction. We also take into account the maximum temperature and the minimum rainfall due to the change of seasons. We have used various machine learning methods to calculate seasonal production, and SVM is the best machine learning method that works best. We will also see that the SVM machine algorithm works very well and gives good results. We calculated what the future would be like in the end after 20 years, and the future temperature will be based on the seasonal temperature scale using the SVM algorithm. In this research, I have also told you the best time according to the agronomist's method and how to produce them.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science Engineering > Machine Learning
Domains: Information Technology
Depositing User: Mr IR Admin
Date Deposited: 28 Aug 2025 06:58
Last Modified: 28 Aug 2025 06:58
URI: https://ir.vistas.ac.in/id/eprint/11007

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