Title :
Project Evaluation of Financial Guarantee Based on Improved Spectral Clustering
Author :
Weiquan Sang ; Xiaoping Zhang ; Hui Li
Author_Institution :
Coll. of Comput. Sci. & Technol., Guizhou Univ., Guiyang, China
Abstract :
Reasonable and right decisions are the keys to the successful financing guarantee project, and the core of decision-making is the correct evaluation. The improved spectral clustering algorithm is used to build the financing guarantee project evaluation model, which can avoid the set of scale factor, and reduce the computational complexity of matrix eigenvalue decomposition. The financing guarantee project evaluation model is established by MATLAB software, and the effectiveness and high efficiency of CMSC can be verified through the trainings and simulation experiments.
Keywords :
computational complexity; decision making; eigenvalues and eigenfunctions; financial data processing; matrix algebra; pattern clustering; project management; CMSC; MATLAB software; computational complexity; decision-making; financial guarantee; financing guarantee project evaluation model; matrix eigenvalue decomposition; spectral clustering; Clustering algorithms; Data models; Indexes; Industries; Mathematical model; Matrix decomposition; Training; Index system; Risk assessment; Spectral clustering; financial guarantee;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.224
