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

Yan Jun Pang; Wei Pan; Kai Di Liu

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 121-122A Supervised Clustering Algorithm Based on...

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

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 121-122)

Pages:

958-963

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.121-122.958

Citation:

Cite this paper

Online since:

June 2010

Authors:

Yan Jun Pang, Wei Pan, Kai Di Liu

Keywords:

Class Representative Point, Classification Weight, Cluster, Fault Mode

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References

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