LS-SVM Key Nodes Identification from Simple Indices and Complex Indices in Aviation Network
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Haiqing Huang, Xusheng Gan, Jingjuan Sun, Shuangyan Chen
Identifying key nodes in aviation network is significant in practice. A key nodes identification method based on Least Square Support Vector Machine (LS-SVM) is proposed for aviation network. Firstly, basic prinple of LS-SVM is introduced for evaluation modeling, then the comprehensive importance of nodes is calculated through complex indices, finally LS-SVM model is established the mapping relationship between the simple indices (as the input) and the comprehensive importance (as the output). The simulation shows that the proposed method is effective and feasible for identifying the key nodes in aviation network.
Aviation Network; Least Square; Support Vector Machine; Key Nodes Identification; Comprehensive importance