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CLC number: TK233, TP274
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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Data-mining massive real-time data in a power plant: challenges, problems and solutions
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CHEN Jian-hong, REN Hao-ren, SHENG De-ren, Li Wei. Data-mining massive real-time data in a power plant: challenges, problems and solutions[J]. Journal of Zhejiang University Science A, 2002, 3(5): 538-542.
@article{title="Data-mining massive real-time data in a power plant: challenges, problems and solutions",
author="CHEN Jian-hong, REN Hao-ren, SHENG De-ren, Li Wei",
journal="Journal of Zhejiang University Science A",
volume="3",
number="5",
pages="538-542",
year="2002",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2002.0538"
}
%0 Journal Article
%T Data-mining massive real-time data in a power plant: challenges, problems and solutions
%A CHEN Jian-hong
%A REN Hao-ren
%A SHENG De-ren
%A Li Wei
%J Journal of Zhejiang University SCIENCE A
%V 3
%N 5
%P 538-542
%@ 1869-1951
%D 2002
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2002.0538
TY - JOUR
T1 - Data-mining massive real-time data in a power plant: challenges, problems and solutions
A1 - CHEN Jian-hong
A1 - REN Hao-ren
A1 - SHENG De-ren
A1 - Li Wei
J0 - Journal of Zhejiang University Science A
VL - 3
IS - 5
SP - 538
EP - 542
%@ 1869-1951
Y1 - 2002
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2002.0538
Abstract: Nowadays, the scale of data normally stored in a database collected by Data Acquisition System (DAS) or Distributed Control System (DCS) in a power plant is becoming larger and larger. However there are abundant valuable knowledge hidden behind them. It will be beyond people's capacity to analyze and understand these data stored in such a scale database. Fortunately data-mining techniques are arising at the historic moment. In this paper, we explain the basic concept and general knowledge of data-mining; analyze the characteristics and research method of data-mining; give some typical applications of data-mining system based on power plant real-time database on intranet.
[1] Chen, J.H., Sheng, D.R., Li, W., Ren, H.R., 2001a. On-line forecasting-validating model of real-time data for turbogenerator operating expert system. Power system engineering, 17(6):375-378.
[2] Chen, J.H., Ren, H.R., Sheng, D.R., Li, W., 2001b. Investigation on knowledge discovery and data mining based on the real-time turbogenerator's monitoring data. Zhejiang electric power, (6):7-10.
[3] Chen, J.H., Li, W., Sheng, D.R., Ren, H.R., 2002. A data fusion method for on-line performance calculation of turbogenerator. Proceedings of the CSEE, 22(5):152-156.
[4] Fayyad, U., Uthurusamy, R. 1996a. Data mining and Knowledge Discovery: Making Sense Out of Data. IEEE Expert, Oct,p.20-25.
[5] Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., 1996b. From Data Mining to Knowledge Discovery: An Overview. In: Faygad U, ed. Advances in Knowledge Discovery and Data Mining, AAAI Press / The MIT Press, p.1-34.
[6] Fayyad, U., 1996c. From Data Mining to Knowledge Discovery: Advances in Knowledge Discovery and Data Mining. AAAI Press/The MIT Press.
[7] Guo, Y., Wang, Y.,1998. Data mining and knowledge discovery in database: a survey. Patten recognition & Artificial Intelligence, 11(3): 292-299.
[8] Pawlak, Z.,1998. Reasoning about data-A rough set prespective. LNAI 1424, Proceeding of RSCTC'98, Warsaw, Springer, 6:25-34.
[9] Wang, L.Q., Tang, C.J., Yu, Z.H., He, X.M., 1998. Web-based Data Mining. Compumter applications 18(10):10-12.
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