A fuzzy clustering algorithm based on interval valued fuzzy sets

Author

HaiZhou Du ; Weiguo Pan

Author_Institution

Coll. of Comput. & Inf. Eng, Shanghai Univ. of Electr. Power, Shanghai, China

fYear

2012

fDate

29-31 May 2012

Firstpage

283

Lastpage

286

Abstract

Due to the continuity of the thermal power plant operating data and information is incomplete; the data of the characterization of the behavioral characteristics of things is often not the exact number, but the number of interval-valued fuzzy sets of data. Aiming at the characteristics of the historical data of thermal power plants, this paper puts forward a fuzzy clustering analysis method based on interval values. Then according to this method, to carry on a fuzzy clustering analysis to the stable state and non-stable-state data of the thermal power plant operating data, Allowing for further analysis of the real operating status of thermal power units will be and to improve unit efficiency, increase power plant economic efficiency and energy conservation, to provide certain information support.

Keywords

energy conservation; fuzzy set theory; pattern clustering; power engineering computing; power generation economics; thermal power stations; energy conservation; fuzzy clustering analysis method; historical data; information support; interval valued fuzzy sets; nonstable-state data; power plant economic efficiency; real operating status; stable state data; thermal power plant operating data; thermal power units; unit efficiency improvement; Clustering algorithms; Data mining; Educational institutions; Fuzzy sets; Power generation; Thermal analysis; Thermal stability; fuzzy clustering; fuzzy sets; interval valued;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on

Conference_Location

Sichuan

Print_ISBN

978-1-4673-0025-4

Type

conf

DOI

10.1109/FSKD.2012.6233955

Filename

6233955