03155nam a22004935i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072001700183072002300200072001500223072001600238100007500254245011300329250001800442264007200460300006600532336002600598337002600624338003600650347002400686490003800710505046800748520094301216650002502159650002902184650001802213650004502231650003102276650002802307700007402335710003402409773002602443776003602469776003602505776003602541830003802577856004602615978-981-97-5323-9DE-He21320251030112906.0cr nn 008mamaa240822s2024    si |    s    |||| 0|eng d  a97898197532397 a10.1007/978-981-97-5323-92doi 4aT57.6-.97 7aKJT2bicssc 7aKJMD2bicssc 7aBUS0490002bisacsh 7aKJT2thema 7aKJMD2thema1 aXie, Naiming.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aGrey Forecastingh[electronic resource] :bMechanism, Models and Applications /cby Naiming Xie, Baolei Wei.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXIII, 200 p. 24 illus., 15 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSeries on Grey System,x2731-49440 a1. Introduction -- 2. Architecture of grey forecasting models -- 3. Mechanism and reduction of grey forecasting models -- 4. Continuous-time grey endogenous forecasting models -- 5. Discrete-time grey endogenous forecasting models -- 6. Continuous-time grey exogenous forecasting models -- 7. Discrete-time grey exogenous forecasting models -- 8. Nonlinear grey forecasting models -- 9. Grey number-oriented forecasting models -- 10. Comments and future thinking.  aThis book aims to present an overview of grey system models for time series modelling and forecasting. It is about modelling and forecasting time series with ordinary differential equations, especially when the available samples are extremely limited. Grey system models (GSM) develop sequence operators to nonparametrically identify the underlying dynamics from the limited observations. This book concerns about two important modelling themes, small sample and poor information. The former focuses on the mechanism and methodology of GSMs for small-sample real-number time series, and the latter on the uncertainty quantification of grey number together with its small-sample modelling principles. In this book, a broad entry point to applied data science for students majoring in economic, management science, and engineering is applied, covering a wide range of topics from basic introductory material up to research-level techniques. 0aOperations research. 0aMathematicsxPhilosophy. 0aEconometrics.14aOperations Research and Decision Theory.24aPhilosophy of Mathematics.24aQuantitative Economics.1 aWei, Baolei.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981975322208iPrinted edition:z978981975324608iPrinted edition:z9789819753253 0aSeries on Grey System,x2731-494440uhttps://doi.org/10.1007/978-981-97-5323-9