This project uses machine learning techniques ... for real-time yield predictions based on user-inputted farming conditions. The trained LightGBM model is deployed using Gradio. Users can input ...

Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms ... Finally, a prospective architecture of machine learning-based palm oil yield ...

Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate yield prediction requires fundamental understanding of the ...

Interactions among different genetic, environmental, and management factors and uncertainty in input values are making crop yield prediction complex. Building upon a previous work in which we coupled ...

The user may forecast the agricultural production in any year they choose using the ... parameters, the predictions provided by learning algorithms will assist farmers in choosing which crop to ...

The "Crop Yield Prediction using Machine Learning" project forecasts agricultural yields by analyzing historical data on crop type, weather, soil quality, and farming practices. It helps farmers ...

Strictly speaking, Machine Learning (ML) is a set of techniques ... to analyse the capability of ML methods for yield prediction in sunflower and wheat using a synthetic dataset obtained with crop ...