Search alternatives:
lower decrease » larger decrease (Expand Search), linear decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
lower decrease » larger decrease (Expand Search), linear decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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3221
Relationship between <i>β</i><sub>1</sub> and <i>β</i><sub>2</sub> and compressive strength.
Published 2024Subjects: -
3222
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3223
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3224
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3225
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3226
Percentage distribution (weighted) of surveyed facilities in 2014 and 2017.
Published 2025Subjects: -
3227
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3228
Textural profile of beef sausage containing different fats and roasted at different temperature.
Published 2025Subjects: -
3229
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3230
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3231
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3232
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3233
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3234
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3235
Structure diagram of ensemble model.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”
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3236
Fitting formula parameter table.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”
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3237
Test plan.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”
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3238
Fitting surface parameters.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”
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3239
Model generalisation validation error analysis.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”
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3240
Empirical model prediction error analysis.
Published 2024“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”