activity
20192021
most citedCoupling Machine Learning and Crop Modeling Improves Crop Yield Prediction in the US Corn Belt

439 citations · 984 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.QM2021

Corn Yield Prediction with Ensemble CNN-DNN

Mohsen Shahhosseini, Guiping Hu, Saeed Khaki +1

We investigate the predictive performance of two novel CNN-DNN machine learning ensemble models in predicting county-level corn yields across the US Corn Belt (12 states). The deve…

cs.LG2020★ 28 cited

Improved Weighted Random Forest for Classification Problems

Mohsen Shahhosseini, Guiping Hu

Several studies have shown that combining machine learning models in an appropriate way will introduce improvements in the individual predictions made by the base models. The key t…

q-bio.QM2020★ 439 cited

Coupling Machine Learning and Crop Modeling Improves Crop Yield Prediction in the US Corn Belt

Mohsen Shahhosseini, Guiping Hu, Sotirios V. Archontoulis +1

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 whether a h…

stat.AP2020★ 277 cited

Forecasting Corn Yield with Machine Learning Ensembles

Mohsen Shahhosseini, Guiping Hu, Sotirios V. Archontoulis

The emerge of new technologies to synthesize and analyze big data with high-performance computing, has increased our capacity to more accurately predict crop yields. Recent researc…

q-bio.OT2019★ 230 cited

Maize Yield and Nitrate Loss Prediction with Machine Learning Algorithms

Mohsen Shahhosseini, Rafael A. Martinez-Feria, Guiping Hu +1

Pre-season prediction of crop production outcomes such as grain yields and N losses can provide insights to stakeholders when making decisions. Simulation models can assist in scen…

stat.ML2019★ 10 cited

Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems

Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Aggregating multiple learners through an ensemble of models aim to make better predictions by capturing the underlying distribution of the data more accurately. Different ensemblin…