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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Measurement and Monitoring Performance Parameters of Next Generation Networks
 Grenar, David ; Vlček, Čestmír (referee) ; Róka,, Rastislav (referee) ; Smékal, Zdeněk (advisor)
The thesis is concentrated on the topic of next generation access networks. In the thesis, first of all, is conducted the analysis of the current state of knowledge with special focus on current technical and legislative developments and trends in access networks. The thesis describes the current structure of access networks and analyzes the current state of the issue of access technology. Measurement and testing methods for its verification depending on the type of network or operation of IP services are also described. Subsequently, the dissertation presents mathematical methods, that can be used in order to assess the access network model. In addition, recommendations and methods for monitoring and modelling access network data are evaluated. In particular, the subject of interest in this thesis is the issue of traffic intensity. The thesis presents a proposal for the construction of a mathematical modelling for the traffic profile and its application.
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Modelling of Traffic Flow with Bayesian Autoregressive Model with Variable Partial Forgetting
 Dedecius, Kamil ; Nagy, Ivan ; Hofman, Radek
Computing the future road traffic intensities in urban and suburban areas is considered inthis paper. The statistical properties of the traffic flow advocate the use of a low-order lin- ear autoregressive models, in which the previous intensities determine the following ones. To achieve adaptivity, the Bayesian modelling framework was chosen. The regression coefficients are considered random, hence they are modelled using a suitable distribution. A significant improvement of the overall modelling performance is further reached with techniques allowing the parameters vary by modification of their distribution. We present the partial forgetting method, allowing to individually track the parameters even in the case of their different variability rate.
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