Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model.

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作者： Dost Muhammad,Khan ^[1] ; Muhammad,Ali ^[1] ; Nadeem,Iqbal ^[2] ; Umair,Khalil ^[3] ; Hassan M,Aljohani ^[1] ; Amirah Saeed,Alharthi ^[4] ; Ahmed Z,Afify ^[4]

作者单位： Department of Statistics, Abdul Wali Khan University Mardan, Mardan, Pakistan. ^[1] Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, Pakistan. ^[2] Division of Computer Science, Mathematics and Science, St John's University, New York, NY, United States. ^[3] Department of Mathematics & Statistics, College of Science, Taif University, Taif, Saudi Arabia. ^[4] Department of Statistics, Mathematics and Insurance, Benha University, Benha, Egypt. ^[5]

关键词 ARIMA COVID-19 augmented Dicky-Fuller test ensemble empirical mode decomposition error trend seasonal model prediction

主题词预测(Forecasting);人类(Humans);模型, 理论(Models, Theoretical);疾病大流行(Pandemics);季节(Seasons)

DOI 10.3389/fpubh.2022.922795

PMID 35968475

发布时间 2022-08-16

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Frontiers in public health

2022年10卷

922795页

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Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model.

Frontiers in public health

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Frontiers in public health

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Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model.

Frontiers in public health

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Frontiers in public health

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