… We extract the time series relationship in the data, and the rolling prediction method is …
ARIMA models for the acceleration of each death function, and found that seasonal changes affect …

… the real situation, so the initial model prediction mainly represents … ARMA method's prediction
only depends on the time series, … COVID-19 has spread rapidly and severely affects human …

… a machine learning method to analyze the impact of four natural disasters, volcanic eruption,
forest fire, COVID-19 and … linear regression prediction model, pro-moted the model with the …

… Time series analysis and predicting COVID⁃19 affected patients by ARIMA model using
machine learning[J].J Virol Methods,2022,301: 114433.DOI: 10.1016/j.jviromet.2021.114433. …

… shortage as an example, due to the Covid-19 pandemic and … ) by incorporating text, time
series, and supply chain networks… the use of modern machine learning models to predict …

… deep learning-based urban travel demand prediction model… EIFC can process the data of
the factors affecting urban travel … ,因此在没有足够数据的情况下可能无法使用ARIMA或SARIMA. …

… Comparison of seven time series models in fitting and predicting the … ,是ARIMA(0,2,2)模型
的一个特例,它为平滑参数提供了一个简单的上限,以确保可逆模型.这种方法相对于完整的ARIMA(0,…

… and its preload degradation or backlash exists will affect the positioning accuracy. In order to
… (GAN) model to deal with ball screw preload data shortage problem, a deep learning-based …

… field of deep learning. RNN has been proved to be an effective tool for processing time series
prediction. … Comparative analysis and forecasting of COVID-19 cases in various European …

… We propose a spatial-temporal-based deep learning … as weather, time, driver, etc.) that affect
the travel time, we have … 所提出的方法已应用于罗马市:通过使用基于ARIMA的模型,在观察到…