This project aims to develop a machine learning based crop-prediction model to support farmers ... The model is built using Deep Neural Networks(DNNs). The architecture we have chosen consists of 3 ...

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 ...

This project aims to develop a machine learning based crop-prediction model to support farmers ... The model is built using Deep Neural Networks(DNNs). The architecture we have chosen consists of 3 ...

Machine learning (ML) algorithms have the potential to surpass the prediction ... using simpler tree-based models with greater potential for interpretability of the results. Nonetheless, 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 ...

Comparative analysis of Machine Learning techniques for Crop prediction. Performance evaluation based on only soil, only environmental characteristics and both. Performance analysis for classifiers ...

the researchers have shattered a longstanding barrier that frustrated computational predictions under complex evolving loads central to 2D material design. Their machine learning architecture not only ...

The user may forecast the agricultural production in any year they choose using the script's simple ... and other parameters, the predictions provided by learning algorithms will assist farmers in ...