← Back to Research Papers
Ready to Publish
Computer Science / AI
AI-Based Crop Yield Prediction Using Machine Learning
Abstract
A research paper presenting an ML model that predicts crop yields using weather, soil and satellite data, with comparative analysis of Random Forest, XGBoost and LSTM approaches.
Price
₹7,999
Delivery
Delivery:
7-10 days
File
Claims:
5
Problem
Farmers lack data-driven yield forecasts; existing models ignore multi-source data fusion.
Solution
The paper proposes a fused-feature pipeline combining weather APIs, soil sensor data and satellite imagery, benchmarked across three ML models with statistical significance testing.
Paper Contents
1
5-page IEEE-format paper with results tables
2
Confusion matrices and ROC curves
3
Dataset description and preprocessing steps
4
Comparative analysis with baseline models
5
Conclusion and future scope
What's Included
Full paper (IEEE format, 5-6 pages)
Plagiarism report below 10%
Dataset details and code logic
Reviewer response draft
Journal formatting