2026-10-11T02:47:09Z https://www.scidb.cn/oai

10.57760/sciencedb.36222 2026-05-08T14:56:41Z

2026-05-08 Dataset for the Identification of Blazar Candidates of Uncertain Type (BCU) Based on Effective Spectral Indices doi:10.57760/sciencedb.36222 en This dataset is the core supporting result data for the paper The Type Recognition of Blazar Candidates of Uncertain Type Based on Effective Spectral Indices. Aiming at 1177 Blazar Candidates of Uncertain type (BCUs) observed by Fermi/LAT, unsupervised classification and recognition were carried out using the Gustafson-Kessel (GK) fuzzy clustering algorithm based on 15 sets of effective spectral indices (αRO, αRX, αRγ, αOX, αOγ, αXγ) from pairwise combinations of four wavebands: radio (R), optical (O), X-ray (X), and γ-ray (γ). Its core content covers source-by-source classification labels for 1177 BCU samples under 15 effective spectral index combinations (label B for BL Lac objects, label F for Flat Spectrum Radio Quasars, FSRQs), statistical results of the number of BCUs classified as BL Lacs and FSRQs under 15 parameter combinations, the final tendency type (CT) of each BCU sample determined by the majority voting principle of multi-group classification results, the accuracy p-value of the classification result for each BCU sample to quantify the confidence level of the classification, as well as supporting core calculation parameters including the GK fuzzy clustering centers of known-type blazars (BL Lacs/FSRQs) and Euclidean closeness degree. This dataset can be widely used in research fields including blazar classification and physical property research, multi-band radiation characteristic analysis of Active Galactic Nuclei (AGNs), and the verification and optimization of unsupervised machine learning algorithms in astronomical object classification. Blazar; BCU; Effective Spectral Index; GK Fuzzy Clustering; AGN; Fermi/LAT; Astronomical Data Liu Bei Yangjiang River Fan Junhui PUBLIC https://creativecommons.org/licenses/by-nc/4.0/ dataset Science Data Bank