Data mining techniques based on grey system theories for time sequence data | Zendy

Bin Liu | Zendy; Hui Zhang | Zendy; Sifeng Liu | Zendy; Yaoguo Dang | Zendy

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Data mining techniques based on grey system theories for time sequence data

Author(s) -

Bin Liu,

Hui Zhang,

Sifeng Liu,

Yaoguo Dang

Publication year - 2006

Publication title -

computer science and information systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.244

H-Index - 24

eISSN - 2406-1018

pISSN - 1820-0214

DOI - 10.2298/csis0602073b

Subject(s) - nomothetic and idiographic , computer science , sequence (biology) , field (mathematics) , data mining , status quo , focus (optics) , data science , mathematics , psychology , social psychology , genetics , physics , economics , pure mathematics , optics , market economy , biology

Data mining is an interesting focus in computer science field now. This paper deals with data mining techniques based on Grey system theories for time sequence data. Firstly, thoughts of data mining with embedded knowledge are expatiated, and the status quo of Data mining techniques is presented briefly. Then, based on the above thoughts and the Grey system theories, data mining techniques based on Grey system theories for time sequence data are proposed for the first time, and the idiographic arithmetic with GM(1,1) as an example is introduced in this paper. Last, it forecasts the total homes in 2002~2005 connecting with Internet in ShangHai City by the arithmetic.

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