Improving the Forecasting of Winter Wheat Yields in Northern China with Machine Learning-Dynamical Hybrid Subseasonal-to-Seasonal Ensemble Prediction.
Junjun CaoHuijing WangJinxiao LiQun TianDev NiyogiPublished in: Remote. Sens. (2022)
Keyphrases
- machine learning
- short term
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- grey model
- stock market prediction
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- prediction accuracy
- neural network ensemble
- random forest
- prediction algorithm
- exponential smoothing
- learning algorithm
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- arima model
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- hong kong
- ensemble learning
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- prediction error
- machine learning methods
- decision trees
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- computational intelligence
- short term load forecasting
- chaotic time series
- training data
- knowledge acquisition
- computer vision
- box jenkins
- random forests
- data analysis
- computer science
- pattern recognition
- reinforcement learning