Related references
Note: Only part of the references are listed.Bayesian Multi-modeling of Deep Neural Nets for Probabilistic Crop Yield Prediction
Peyman Abbaszadeh et al.
AGRICULTURAL AND FOREST METEOROLOGY (2022)
Development of crop yield forecast models under FASAL- a case study of kharif rice in West Bengal
K. GHOSH et al.
Journal of Agrometeorology (2022)
Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring
Gopal Krishna et al.
GEOCARTO INTERNATIONAL (2021)
DeepYield: A combined convolutional neural network with long short-term memory for crop yield forecasting
Keyhan Gavahi et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Comparison of Lasso and stepwise regression technique for wheat yield prediction
SUDHEER KUMAR et al.
Journal of Agrometeorology (2021)
Optimal county-level crop yield prediction using MODIS-based variables and weather data: A comparative study on machine learning models
Sungha Ju et al.
AGRICULTURAL AND FOREST METEOROLOGY (2021)
Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods
Elisa Kamir et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)
Prediction of Winter Wheat Yield Based on Multi-Source Data and Machine Learning in China
Jichong Han et al.
REMOTE SENSING (2020)
Comparative evaluation of linear and nonlinear weather-based models for coconut yield prediction in the west coast of India
Bappa Das et al.
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY (2020)
Application of Artificial Neural Network for Predicting Maize Production in South Africa
Omolola M. Adisa et al.
SUSTAINABILITY (2019)
A Comparison Between Major Artificial Intelligence Models for Crop Yield Prediction: Case Study of the Midwestern United States, 2006-2015
Nan Kim et al.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2019)
Simulation of maize evapotranspiration: An inter-comparison among 29 maize models
Bruce A. Kimball et al.
AGRICULTURAL AND FOREST METEOROLOGY (2019)
A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide
Jie Chen et al.
ENVIRONMENT INTERNATIONAL (2019)
Multimodel ensembles improve predictions of crop-environment-management interactions
Daniel Wallach et al.
GLOBAL CHANGE BIOLOGY (2018)
Evaluation of multiple linear, neural network and penalised regression models for prediction of rice yield based on weather parameters for west coast of India
Bappa Das et al.
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY (2018)
Accurate prediction of sugarcane yield using a random forest algorithm
Yvette Everingham et al.
AGRONOMY FOR SUSTAINABLE DEVELOPMENT (2016)
Near-Infrared Calibration of Soluble Stem Carbohydrates for Predicting Drought Tolerance in Spring Wheat
Julia L. Piaskowski et al.
AGRONOMY JOURNAL (2016)
The effect of tuning, feature engineering, and feature selection in data mining applied to rainfed sugarcane yield modelling
Felipe F. Bocca et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)
Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter
A. Suleiman et al.
ENVIRONMENTAL MODELING & ASSESSMENT (2016)
Random Forests for Global and Regional Crop Yield Predictions
Jig Han Jeong et al.
PLOS ONE (2016)
Spectral libraries for quantitative analyses of tropical Brazilian soils: Comparing vis-NIR and mid-IR reflectance data
Fabricio S. Terra et al.
GEODERMA (2015)
Predictive ability of machine learning methods for massive crop yield prediction
Alberto Gonzalez-Sanchez et al.
SPANISH JOURNAL OF AGRICULTURAL RESEARCH (2014)
Uncertainty in simulating wheat yields under climate change
S. Asseng et al.
NATURE CLIMATE CHANGE (2013)
Antioxidant properties and chemical composition of technical Cashew Nut Shell Liquid (tCNSL)
Teresinha de Jesus Aguiar dos Santos Andrade et al.
FOOD CHEMISTRY (2011)
Ability to forecast unsteady aerodynamic forces of flapping airfoils by artificial neural network
Dilek Funda Kurtulus
NEURAL COMPUTING & APPLICATIONS (2009)
Building Predictive Models in R Using the caret Package
Max Kuhn
JOURNAL OF STATISTICAL SOFTWARE (2008)
Summarizing multiple aspects of model performance in a single diagram.
KE Taylor
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2001)
Identification of regional soil quality factors and indicators: I. Central and southern high plains
JJ Brejda et al.
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2000)