MACHINE LEARNING APPROACH FOR INDIAN CROP YIELD PREDICTION

Dr.S.Erana Veerappa Dinesh; M. Anusuya; M. Vanneeswari

MACHINE LEARNING APPROACH FOR INDIAN CROP YIELD PREDICTION

Authors: Dr.S.Erana Veerappa Dinesh, M. Anusuya, M. Vanneeswari

Unique Paper ID: 155207
Volume: 9
Issue: 1
PageNo: 141-147

Keywords: Crop Recommendation CNN Data Analysis Decision tree Logistic regression Machine Learning Random Forest.

Abstract:
In today's world, technology plays a critical part in overcoming challenges and achieving better and maximal results in a variety of fields. The agricultural sector in India has a significant impact on the economy. Agriculture employs half of the country's population. The agriculture business is heavily influenced by its surroundings'Â natural circumstances, and as a result, it faces a number of difficulties in terms of actual farming techniques. Agriculture techniques in the country are generally ad hoc, and technological advancement is modest. In this industry, effective technology can be employed to boost yield while minimizingÂ the challenges. Farmers typically sow crops based on their market value and potential yield.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 9
Issue: 1
PageNo: 141-147

MACHINE LEARNING APPROACH FOR INDIAN CROP YIELD PREDICTION

Available:https://ijirt.org/Article?manuscript=155207

31 May, 2022

Credit Card Fraud Detection Using Machine Learning

26 May, 2022

The controllability and preventive measures in Pressure Ulcer based on healthy food and good practices

05 May, 2022

Challenges and improvements in Smart Bed for Bedsore patient and bedridden patients

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry