Art

J-GLOBAL ID：202002268353643873   Reference number：20A2544468

Combined Methodology for Linear Time Series Forecasting

線形時系列予測のための組合せ方法論

Author (3)： Moraes Muniz da Silva Ricardo (Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan) ,  Kugler Mauricio (Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan) ,  Umezaki Taizo (Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan)
Material： IEEJ Transactions on Electrical and Electronic Engineering  (IEEJ Trans Electr Electron Eng)
Volume： 15  Issue： 12  Page： 1780-1790  Publication year： Dec. 2020 
JST Material Number： W1854A  ISSN： 1931-4973  Document type： Article
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Thesaurus term： forecast ,  time series analysis ,  *ARMA model ,  *moving average method ,  *autoregressive model ,  error (measure) ,  combinatorial analysis ,  mathematical model ,  prediction model ,  set ,  data ,  memory (computer) ,  quantitative model ,  Dataset ,  Auto Regressive Integrated Moving Average model ,  *Auto Regressive Fractionally Integrated Moving Average model ,  model
Semi thesaurus term： *線形時系列予測 ,  ARIMA ,  *Auto Regressive Fractionally Integrated Moving Average ,  組合せモデル ,  累積誤差

Author keywords (5)： time series forecasting ,  ARIMA ,  ARFIMA ,  combined model ,  accumulative error

JST classification (1)： Mathematical programmings  (KA03030M)

Terms in the title (4)： 線形 ,  時系列予測 ,  組合せ ,  方法論