Search alternatives:
significant treatment » significant investment (Expand Search), significant enrichment (Expand Search), significant impairment (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
treatment decrease » treatment decreased (Expand Search), treatments decreased (Expand Search), treatment increases (Expand Search)
significant treatment » significant investment (Expand Search), significant enrichment (Expand Search), significant impairment (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
treatment decrease » treatment decreased (Expand Search), treatments decreased (Expand Search), treatment increases (Expand Search)
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4321
Parameter optimization results of BiLSTM.
Published 2025“…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. …”
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4322
Descriptive statistical analysis of data.
Published 2025“…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. …”
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4323
The MAE value of the model under raw data.
Published 2025“…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. …”
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4324
Three error values under raw data.
Published 2025“…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. …”
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4325
Panel quantile regression results.
Published 2024“…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. …”
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4326
Decomposition of time scries plot.
Published 2025“…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. …”
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4327
Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry
Published 2025“…In Ion Mobility Spectrometry (IMS), ion gates are essential for controlling ion flow, significantly impacting detection sensitivity and resolution. …”
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4328
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4329
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4330
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4331
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4332
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4333
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4334
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4335
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4336
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4338
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4339
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4340