بدائل البحث:
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
predicted decrease » predicted secreted (توسيع البحث), reported decrease (توسيع البحث)
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
predicted decrease » predicted secreted (توسيع البحث), reported decrease (توسيع البحث)
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261
Flowchart of the STL-PCA-BWO-BiLSTM model.
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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262
Parameter optimization results of BiLSTM.
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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263
Descriptive statistical analysis of data.
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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264
The MAE value of the model under raw data.
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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265
Three error values under raw data.
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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266
Decomposition of time scries plot.
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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267
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268
Assessing Bivalves as Biomonitors of Per- and Polyfluoroalkyl Substances in Coastal Environments
منشور في 2025"…Despite the ecological and economic significance of coastal environments, monitoring efforts to identify PFAS in these regions are limited. …"
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269
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270
Comparison of the cohesion ranges of different food categories under IDDSI levels.
منشور في 2025الموضوعات: -
271
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272
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273
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274
Comparison of adhesiveness ranges for different food categories under IDDSI levels.
منشور في 2025الموضوعات: -
275
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276
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277
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278
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279
Statistical analysis of adhesiveness, hardness, and cohesiveness across IDDSI levels.
منشور في 2025الموضوعات: -
280
Comparison of hardness ranges for different food categories under IDDSI levels.
منشور في 2025الموضوعات: