Parameter optimization results of BiLSTM. by Xiangjuan Liu (618000)

“…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. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Descriptive statistical analysis of data. by Xiangjuan Liu (618000)

“…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. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

The MAE value of the model under raw data. by Xiangjuan Liu (618000)

“…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. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Three error values under raw data. by Xiangjuan Liu (618000)

“…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. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Panel quantile regression results. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Decomposition of time scries plot. by Xiangjuan Liu (618000)

“…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. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry by Jiyao Wang (2121157)

“…In Ion Mobility Spectrometry (IMS), ion gates are essential for controlling ion flow, significantly impacting detection sensitivity and resolution. …”

AO/EtBr Staining of Cancer cell lines: <i>To check whether vitamin D3 promoted cell death in cancer cells, a dual staining protocol was implemented as detailed in the methods secti... by Vidya G. Bettada (22208808)

Experimental Conditions of Fixed Spray hole diameter. by Lei Bai (631944)

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Average ignition delay time in each temperature range. by Lei Bai (631944)

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Fractal dimension of flame based on box counting method. by Lei Bai (631944)

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Relationship between hot surface temperature and ignition delay time. by Lei Bai (631944)

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Relationship between ignition delay time and spray hole diameter. by Lei Bai (631944)

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Relationship between fuel quantity and ignition delay time. by Lei Bai (631944)

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Relationship between Hot Surface Temperature and Ignition Event. by Lei Bai (631944)

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Fractal dimension evolution of oil droplet flame under different spray hole diameter. by Lei Bai (631944)

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Evolution of flame fractal dimension of oil droplets with different volumes. by Lei Bai (631944)

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Global average ignition delay time of oil droplets with volume of 0.1-0.5ml. by Lei Bai (631944)

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Global average ignition delay time of oil droplets with diameter of 0.4-0.7 mm. by Lei Bai (631944)

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Physical parameters of engine lubricating oil. by Lei Bai (631944)

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