التفاصيل البيبلوغرافية
| العنوان: |
Utilizing machine learning for crop recommender system. |
| المؤلفون: |
Gadipe, Sunitha, Mucha, Swetha, Poladi, Supraja, Thota, Sruthi, Mahesh, Akarapu, Tallapally, Sampath Kumar, Reddy, I. Rajasri |
| المصدر: |
AIP Conference Proceedings; 2024, Vol. 2971 Issue 1, p1-13, 13p |
| مصطلحات موضوعية: |
RECOMMENDER systems, SUPPORT vector machines, K-nearest neighbor classification, AGRICULTURAL industries, CROP yields, BLACKBERRIES |
| مصطلحات جغرافية: |
INDIA |
| مستخلص: |
Rural India's economy is mostly based on agriculture and its related industries. Agriculture has a big impact on the country's GDP (GDP). A blessing in disguise, the country's agricultural sector is a boon. In compared to worldwide norms, the yield per hectare of crops is disappointing. This might explain why marginal farmers in India commit suicide at greater rates than their non-farming counterparts. An easy-to-use yield forecast method for farmers is presented in this study Farmers will be able to connect to the planned system through a smartphone application. GPS aids in pinpointing a user's exact position. The region and soil type are entered by the user. The most lucrative crop list may be picked using machine learning techniques, or the crop yield of a user-selected crop can be predicted. There are various AI techniques that might be utilized to make forecasts about crop efficiency, including support vector machines, fake brain organizations, arbitrary timberlands, multivariate direct relapses, and K-Nearest Neighbors. The Random Forest was the most accurate, coming in at 95%. In addition, the algorithm recommends when to apply fertiliser to maximise production. [ABSTRACT FROM AUTHOR] |
|
Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
Find this article in full text from Scitation.