بدائل البحث:
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
significant factor » significant factors (توسيع البحث)
significant anti » significant health (توسيع البحث), significant change (توسيع البحث), significant amount (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
significant factor » significant factors (توسيع البحث)
significant anti » significant health (توسيع البحث), significant change (توسيع البحث), significant amount (توسيع البحث)
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Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013.
منشور في 2025الموضوعات: -
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Testing set error.
منشور في 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.
منشور في 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.
منشور في 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.
منشور في 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.
منشور في 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.
منشور في 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. …"