论文信息 - The selection of arc spectral line of interest based on improved K-medoids algorithm

The selection of arc spectral line of interest based on improved K-medoids algorithm

In order to eliminate the effect of wavelength error value and spectral line broadening on the definition of arc plasma spectrum, K-medoids algorithm is used to cluster different kinds of spectral lines and determine the spectral line of interest(SLOI). An improved K-medoids algorithm based on minimum spanning tree is proposed to solve the problem that K-medoids algorithm can not ascertain the number of classification. Moreover, spectral distance(SD) is proposed as the criterion to cluster in terms of the characteristic of spectral data. By marking the known spectral lines, cluster testing is made to validate the validity of the algorithm. The experiment results show that improved K-medoids algorithm can cluster effectively and determine the SLOI.

Di Wu | Shan-Ben Chen | Yinshui He | Yiming Huang | Na Lv

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