A Supervised Clustering Algorithm Based on Representative Points and its Application to Fault Diagnosis of Diesel Engine

Abstract:

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By terms of extracting quantization values of each index making contributions to classification, this paper defines index classification weight; and also defines class representative points, weighted distance between samples and representative points; provides an iterative algorithm of searching class representative points, establishes a supervised clustering method based on representative points and it is apply into Fault diagnosis of Diesel Engine.

Info:

Periodical:

Advanced Materials Research (Volumes 121-122)

Edited by:

Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo

Pages:

958-963

DOI:

10.4028/www.scientific.net/AMR.121-122.958

Citation:

Y. J. Pang et al., "A Supervised Clustering Algorithm Based on Representative Points and its Application to Fault Diagnosis of Diesel Engine", Advanced Materials Research, Vols. 121-122, pp. 958-963, 2010

Online since:

June 2010

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Price:

$35.00

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