Title :
Modeling analysis for the temperature system using rough sets
Author :
Xie, Keming ; Yang, Jing ; Lin, T.Y.
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., China
Abstract :
The knowledge reduction algorithm of rough sets (RS) theory is employed to qualitatively analyze the main working condition factors, which influence the model parameters of a superheated steam temperature system in modeling. After reduction, the data that reduced from 19 to 4 clearly shows the relationship between the factors and the parameters. Then, a different classification method was used to classify the decision attributes, and the result shows that different attribute classifications will simplify the problem but not change the property of the problem
Keywords :
boilers; decision theory; rough set theory; uncertain systems; uncertainty handling; classification method; decision attributes; knowledge reduction algorithm; modeling analysis; superheated steam temperature system; Algorithm design and analysis; Artificial intelligence; Character recognition; Educational institutions; Employee welfare; Intelligent control; Power generation; Process control; Rough sets; Temperature;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893431
