摘要
For complex networks, their effectiveness and invulnerability are extremely important. With the development of complex networks, how to evaluate the effectiveness and invulnerability of these networks becomes an important research topic. The relationship among many influencing factors is very complicated, so it is essential to confirm the weighting coefficient of these influencing factors. Principal component analysis(PCA) is proposed to evaluate the performance of complex networks. It can improve one-sidedness of the single evaluation index and select different evaluation models according to different complex networks, which make the evaluation result more accurate. Performance of complex networks can be predicted according to comprehensive evaluation model. To verify the rationality and validity of this method, several small-world networks with different probability values and scale-free network are chosen to evaluate the network performance. Finally, simulation results show that PCA can be applied to performance evaluation of complex networks.
For complex networks, their effectiveness and invulnerability are extremely important. With the development of complex networks, how to evaluate the effectiveness and invulnerability of these networks becomes an important research topic. The relationship among many influencing factors is very complicated, so it is essential to confirm the weighting coefficient of these influencing factors. Principal component analysis(PCA) is proposed to evaluate the performance of complex networks. It can improve one-sidedness of the single evaluation index and select different evaluation models according to different complex networks, which make the evaluation result more accurate. Performance of complex networks can be predicted according to comprehensive evaluation model. To verify the rationality and validity of this method, several small-world networks with different probability values and scale-free network are chosen to evaluate the network performance. Finally, simulation results show that PCA can be applied to performance evaluation of complex networks.
基金
supported by the National Natural Science Foundation of China(61877067,61572435)
the Joint Fund Project of the Ministry of Education-the China Mobile(MCM20170103)
Xi'an Science and Technology Innovation Project(201805029YD7CG13-6)
Ningbo Natural Science Foundation(2016A610035,2017A610119)
