Design method of campus network structure robustness
- 10.2991/amcce-15.2015.271How to use a DOI?
- BP neural network; variable weight; robustness; network
the traditional design of campus network adopts BP neural network to build the model for evaluating network information of network model, since the information exchange reflected in campus network is between individual and individual, randomness and model property factors of network information are prominent, BP neural network weights into curing condition, causes the information trust degree evaluation of large error. This paper presents an optimized robustness node design model, to construct information trust evaluation model. Setting up the trust degree respond weighting variable adaptive function periodically by adjusting network topologic weight vector, effectively reduce the operational cost of the iterative algorithm, and construct campus robust network. Simulation results show that, the new network information robustness evaluation model can reduce error rate of the website information evaluation greatly, the system has strong stability and robustness, can effectively promote the sound operation and development of network.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lin Zhu PY - 2015/04 DA - 2015/04 TI - Design method of campus network structure robustness BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.271 DO - 10.2991/amcce-15.2015.271 ID - Zhu2015/04 ER -