[HTML][HTML] Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …
evaluation at the field level for determining strategic plans in agricultural commodities for …
[HTML][HTML] Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt
This study investigates whether coupling crop modeling and machine learning (ML)
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …
[HTML][HTML] The application of multiple linear regression and artificial neural network models for yield prediction of very early potato cultivars before harvest
Yield forecasting is a rational and scientific way of predicting future occurrences in
agriculture—the level of production effects. Its main purpose is reducing the risk in the …
agriculture—the level of production effects. Its main purpose is reducing the risk in the …
[HTML][HTML] Distance-entropy: an effective indicator for selecting informative data
Smart agriculture is inseparable from data gathering, analysis, and utilization. A high-quality
data improves the efficiency of intelligent algorithms and helps reduce the costs of data …
data improves the efficiency of intelligent algorithms and helps reduce the costs of data …
[HTML][HTML] Prediction of winter wheat yield and dry matter in North China Plain using machine learning algorithms for optimal water and nitrogen application
Y Wang, W Shi, T Wen - Agricultural Water Management, 2023 - Elsevier
Accurate prediction of crop yield and dry matter as well as optimized water and nitrogen
management can favor rational decision-making for farming systems. Combining high …
management can favor rational decision-making for farming systems. Combining high …
[HTML][HTML] A county-level soybean yield prediction framework coupled with XGBoost and multidimensional feature engineering
Yield prediction is essential in food security, food trade, and field management. However,
due to the associated complex formation mechanisms of yield, accurate and timely yield …
due to the associated complex formation mechanisms of yield, accurate and timely yield …
Price forecasts of ten steel products using Gaussian process regressions
X Xu, Y Zhang - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Addressing price forecasting problems is an important exercise to policymakers and market
participants in the resource business sector. In this work, we build Gaussian process …
participants in the resource business sector. In this work, we build Gaussian process …
WheatNet: A lightweight convolutional neural network for high-throughput image-based wheat head detection and counting
For a globally recognized plant breeding organization, manually recorded field observation
data is crucial for plant breeding decision making. However, certain phenotypic traits such …
data is crucial for plant breeding decision making. However, certain phenotypic traits such …
Forecasting wholesale prices of yellow corn through the Gaussian process regression
B Jin, X Xu - Neural Computing and Applications, 2024 - Springer
For market players and policy officials, commodity price forecasts are crucial problems that
are challenging to address due to the complexity of price time series. Given its strategic …
are challenging to address due to the complexity of price time series. Given its strategic …