Research of Clustering Algorithm Based on Different Data Field Model

Hai Dong Meng; Peng Fei  Wu; Yu Chen  Song; Guan Dong Xu

doi:10.4028/www.scientific.net/AMR.760-762.1925

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 760-762Research of Clustering Algorithm Based on...

Research of Clustering Algorithm Based on Different Data Field Model

Abstract:

Data field clustering algorithm possesses dynamic characteristics compared with other clustering algorithms. By changing the parameters of the data field model, the results can be dynamically adjusted to meet the target of feature extraction and knowledge discovery in different scales, but the selection and construction of data field model can give rise to different clustering results. This paper presents the different effectiveness of clustering based on various of data field models and its parameters, provides with the scheme to chose the best data field model fitting to the characteristics of the data radiation, and verifies that the best clustering effectiveness can be achieved with the value of radial energy in the golden section.

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Periodical:

Advanced Materials Research (Volumes 760-762)

Pages:

1925-1929

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.760-762.1925

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Online since:

September 2013

Authors:

Hai Dong Meng, Peng Fei Wu, Yu Chen Song, Guan Dong Xu

Keywords:

Data Field Clustering, Data Field Models, Golden Section, Radial Energy

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