Crop Yield Prediction Using Machine Learning Technologies
Author(s):
CH. Preethi, N. Likhitha Reddy, B. Mounika, J. Alisha Reddy
Keywords:
Crop_yield_prediction, Machine Learning, Naive Bayes, K Nearest Neighbor.
Abstract
The primary thing that is essential for survival is agriculture. A key viewpoint for finding a practical and real-world solution to the crop production issue is machine learning (ML). It primarily focuses on estimating the crop yield using a variety of machine learning approaches. Here, Naive Bayes and K Nearest Neighbor are utilised as classifier models, which aid in delivering the highest level of accuracy. By taking into account variables like temperature, soil, rainfall, acreage, etc., the predictions provided by machine learning algorithms will assist farmers in choosing which crop to cultivate to induce the greatest yield. This ties the technology and agricultural sectors together.
Article Details
Unique Paper ID: 156263

Publication Volume & Issue: Volume 9, Issue 3

Page(s): 224 - 225
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies