APPLICATION OF NEURO-FUZZY APPROACH TO IMPROVE RELIABILITY AND OPTIMAL WORK OF COMPUTER NETWORK
DOI:
https://doi.org/10.15673/0453-8307.1/2014.32663Keywords:
neuro-fuzzy network, adaptive routing, intelligent prediction, neural network, training of the network, matrix algorithm, self-learning network, learning rules, activation function, hybrid network, optimal route.Abstract
The paper presents analysis of the existing traditional methods of finding the best route for routing in networks. As an alternative to the traditional method, was proposed a neuro-fuzzy approach for the optimization of the routing process with the prediction of failure of the server's hard disk drive. For the prediction we used the package FuzzyTech environment Matlab. The program that is based on the unit neuro-fuzzy logic was written. The initial data are taken data corporation Google, which was published at a conference in Toronto. Based on these data, the predicted probability of failure of the hard disk server, resulting in changes in the architecture of a corporate network, and consequently bring changes in the routing process. Specific advantages of the neuro-fuzzy method over the traditional, namely, accounting expert opinion, the ability to self-learning and the ability to work with non-linear functions.
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