Abstract
Because the continuity and information of the operating data of thermal power plant are incomplete, the data representing object’s behavioral characteristics are often not certain numbers, but some interval values. 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, and to make a quantitative analytical judgment, thus to further analyze the objective and real situation of the running status of a thermal power generator, which will facilitate operating personnel to improve unit efficiency, and be useful to support energy saving and emission reduction for the power plant.
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Du, H. (2011). Study of a Fuzzy Clustering Algorithm Based on Interval Value. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23971-7_20
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DOI: https://doi.org/10.1007/978-3-642-23971-7_20
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