Comparison of post-experimental outcome measures. حسب Neng Pan (5262032)

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Mineral component content. حسب Chuan Li (158692)

"…Furthermore, the formation and propagation of these thermal cracks significantly influence macroscopic mechanical properties. …"

Micro-parameters of the numerical model. حسب Chuan Li (158692)

"…Furthermore, the formation and propagation of these thermal cracks significantly influence macroscopic mechanical properties. …"

Microcracks on the surface of the coal sample. حسب Chuan Li (158692)

"…Furthermore, the formation and propagation of these thermal cracks significantly influence macroscopic mechanical properties. …"

Flowchart of the test. حسب Chuan Li (158692)

"…Furthermore, the formation and propagation of these thermal cracks significantly influence macroscopic mechanical properties. …"

Distribution of thermal cracks. حسب Chuan Li (158692)

"…Furthermore, the formation and propagation of these thermal cracks significantly influence macroscopic mechanical properties. …"

Experimental data support. حسب Quan Shen (37564)

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Test specimen. حسب Quan Shen (37564)

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Physical and Mechanical Properties of Red Clay. حسب Quan Shen (37564)

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Roadyes-modified red clay water content limits. حسب Quan Shen (37564)

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Effect of three substances on clay shear strength. حسب Quan Shen (37564)

الموضوعات:

Influence of Roadyes on red clay shear strength. حسب Quan Shen (37564)

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Particle size distribution curve. حسب Quan Shen (37564)

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Experimental Design. حسب Quan Shen (37564)

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Field Site of Red Clay Subgrade Diseases in Zhuzhou. حسب Quan Shen (37564)

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EMI of 0.25% Roadyes-treated red clay after failure. حسب Quan Shen (37564)

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Testing set error. حسب Xiangjuan Liu (618000)

"…<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. …"

Internal structure of an LSTM cell. حسب Xiangjuan Liu (618000)

"…<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. …"

Prediction effect of each model after STL. حسب Xiangjuan Liu (618000)

"…<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. …"

The kernel density plot for data of each feature. حسب Xiangjuan Liu (618000)

"…<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. …"