Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant factor » significant factors (Expand Search)
significant co » significant _ (Expand Search), significant gap (Expand Search), significant cause (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant factor » significant factors (Expand Search)
significant co » significant _ (Expand Search), significant gap (Expand Search), significant cause (Expand Search)
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Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013.
Published 2025Subjects: -
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Testing set error.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”
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Internal structure of an LSTM cell.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”
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Prediction effect of each model after STL.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”
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The kernel density plot for data of each feature.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”
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Analysis of raw data prediction results.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”
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Flowchart of the STL.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”