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Updated: May 20, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
Published on: August 19, 2021
[A soft discretization method of celestial spectrum characteristic line based on fuzzy C-means clustering]
Ji-fu Zhang1, Xin Li, Hai-feng Yang
1School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China. jifuzh@sina.com
Abstract:
Discretization of continuous numerical attribute is one of the important research works in the preprocessing of celestial spectrum data. For characteristic line of celestial spectrum, a soft discretization algorithm is presented by using improved fuzzy C-means clustering. Firstly, candidate fuzzy clustering centers of characteristic line are chosen by using density values of sample data, so that its anti-noise ability is improved. Secondly, parameters in the fuzzy clustering are dynamically adjusted by taking compatibility of decision table as criteria, so that optimal discretization effect of the characteristic line is achieved. In the end, experimental results effectively validate that the algorithm has higher correct recognition rate of the algorithm by using three SDSS celestial spectrum data sets of high-redshift quasars, late-type star and quasars.
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