Crop Yield Estimator for Smart Agriculture using Machine Learning

Hemamalini S , Suraksha. M , Sreya. S , Sowmiya. R , Dhanushiya.K.S

Crop yield prediction, Machine learning (ML), Agriculture, Long Short-Term Memory Networks (LSTM), Random Forest, Stochastic Gradient Descent (SGD,) Decision Tree, Gradient Boosting, K-nearest Neighbour (KNN).

Agriculture practices will have a significant impact on the well-being of Indian citizens in the future. A sustainable food supply can be ensured using machine learning, and farmers can stay informed about the most recent weather patterns. In a recent study, researchers looked into how to discover agricultural yield prediction models using artificial intelligence approaches. Because of the nonlinear relationship between the input and output variables, the system of supervised learning, widely used to evaluate fruits, was ineffective. Even though these methods improve the accuracy of crop yield prediction, they are expensive. The application of ML approaches to predict crop productivity has been discovered in an increasing number of studies. This paper provides a thorough analysis of the precision of various ML models to investigate their efficacy. This study intends to investigate how machine learning can be used to forecast crop yield. Various machine learning (ML) algorithms such as Regression, Decision trees, etc are evaluated based on their performance.

Published Paper   E-Certificate

"Crop Yield Estimator for Smart Agriculture using Machine Learning", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.184-189, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001029.pdf

Volume 11 Issue 2, February-2024

Pages : 184-189

Paper Reg. ID: TIJER_150980

Published Paper Id: TIJERB001029

Downloads: 000299

Research Area: Science and Technology

Country: THIRUVALLUR, TAMILNADU, India

Published Paper PDF: https://tijer.org/TIJER/papers/TIJERB001029

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJERB001029

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: TIJER (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition