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Using Partial Least Squares Method To Evaluate Signaling Load

Posted on:2018-07-24Degree:MasterType:Thesis
Country:ChinaCandidate:J L HanFull Text:PDF
GTID:2357330542953400Subject:Statistics
Abstract/Summary:PDF Full Text Request
This paper describes the use of R software package pls partial least squares modeling approach, based on the "Distributed Home Subscriber Server" the multi-interface signaling data and signaling unit CPU load data, mobile users VoLTE business users. quantify behavior, generating user traffic model to evaluate the number and types of signaling traffic of different user corresponding to the model as independent variables, the "distributed home subscriber server" signaling processing unit CPU load as the dependent variable bias modeling and least squares regression fit.As a core algorithm "Distributed Home Subscriber Server Evaluation data prediction scheme" in the rapid deployment of VoLTE business environment, the network burst disaster scene,assessment, prediction they have practical value, so as to achieve "market-oriented and business-oriented view, fine for network operation and maintenance management "goal.The paper is structured as followsChapter One Introduction:Full description of the background of the subject in which the mobile communication network VoLTE business rapid deployment, indicating their real value and source of demand scenarios, based on this quick introduction to the subsequent analysis of the content.This section describes the evolution of the present situation and the direction of VoLTE technology program also introduced distributed home subscriber data server location and role in the network topology.Chapter TWO Data sources and descriptive analysis:It describes how to obtain the required data and the data on the specified device DHSS practical significance.How to obtain data preprocessing.Chapter ? Partial Least Squares:Schematic explanation partial least squares method..R for language shows how data obtained partial least squares analysis.Chapter ? DHSS signaling load evaluation model:Explain how to use the R software PLS package, use the"Partial Least Squares" DHSS signaling device count formodeling, analysis and backtracking.Chapter ? Conclusion and Outlook:Conclusive results of the analysis described, the system described in this paper discussed the method of technical guidance and promote the value of commercial real work.Chapter ? References:...
Keywords/Search Tags:partial least squares regression, regression analysis, VoLTE, Distributed Home Subscriber Server(DHSS), Signaling load evaluation system
PDF Full Text Request
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