This study explores the development of two predictive models for the yield sooting index (YSI) of various fuels using the advanced capabilities of machine learning (ML), particularly multilayer ...

Machine learning techniques to develop a system for crop recommendation and yield prediction, aimed at supporting data-driven agricultural decision-making. Exploratory data analysis (EDA) is conducted ...

Accurate crop yield prediction is critical for global food security, economic planning, and insurance modeling. Traditional process-based (PB) models rely on biophysical equations and empirical data, ...

Data Preprocessing: Cleaning, normalizing, and integrating data for effective analysis. Model Development: Employing machine learning models (e.g., LSTM, ARIMA, SVM) for weather prediction, crop ...

Crop Yield Prediction Using Federated Learning This is the official documentation of the code repository of the paper: Patrick Killeen, Iluju Kiringa, and Tet Yeap "UAV Imagery-Based Yield Prediction ...

A new machine-learning model for predicting crop yield using environmental data and genetic information can be used to develop new, higher-performing crop varieties.

The Internet of Things (IoT) and machine learning (ML) are two of the most rapidly expanding academic areas. “Smart x” systems that utilize ML and IoT include smart houses, smart cars, smart campuses, ...

Keywords: crop production, crop prediction, agricultural data processing, machine learning, ensemble learning Citation: Hasan M, Marjan MA, Uddin MP, Afjal MI, Kardy S, Ma S and Nam Y (2023) Ensemble ...