Performance Evaluation for Engineering Project Management of Particle Swarm Optimization Based on Least Squares Support Vector Machines
Dong Qiao-Ting, Geng Li-Yan, SHEN Ying-Ming
Journal of Networking Technology, Vol. 7, No. 1, 2016.
DOI: 
Link: http://www.dline.info/jnt/fulltext/v7n1/v7n1_1.pdf
Abstract:
As for the limitation of using cross validation method to choose the parameters of least squares support
vector machines (LSSVM), this paper proposes a new classified model which combines adaptive particle swarm
optimization (APSO) algorithm with LSSVM. The new model uses APSO algorithm to select optimal parameters for
LSSVM. According to the analysis of the management performance evaluation for engineering project, we conclude that
LSSVM-APSO has better evaluation performance than LSSVM which bases on cross validation method. On searching
for the optimal parameters of LSSVM, APSO algorithm is obviously faster than that by cross validation method.