Earticle

초록

영어

Computer network is one of the world's most important infrastructures in twenty-first Century, network fault diagnosis has become the focus of attention. With the development of artificial intelligence, using the neural network technology into the network fault diagnosis area can play an important role to the advantages of neural network in fault diagnosis. In this paper, the method is widely used, which is combined the self organizing feature map (SOM) neural network and multilayer feedforward neural network (BP): The result of the training samples using SOM neural network clustering algorithm is added to the original training samples and set a certain weight, through iterative update to the weight, in order to improve the convergence the speed of BP neural network. Using computer network fault diagnosis as a practical example for the computer simulation and analysis developes a set of computer network diagnosis system can provide reference and assistance for the work of theory research and application.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Proposed Scheme
  3.1. SOM Neural Network Model
  3.2. Application of Neural Network Fault Diagnosis
 4. Experimental Results and Analysis
 5. Conclusion
 References

키워드

저자

• Wang Qian [ Zibo Vocational Institute, Zibo, China, 255314 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605