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Research On Swarm-Based Modeling And Simulation For Telecom Clients Prediction

Posted on:2008-06-05Degree:MasterType:Thesis
Country:ChinaCandidate:X WangFull Text:PDF
GTID:2178360245978463Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
The telecom market is a complex system with the characteristics of large scale, complicate structure, non-linear. It is hard to describe and analyze them with the math methods or other formalized methods. However, those problems have been settled by the mrthod of systemic modeling and simulation. This paper deals with these problems according to the theory of system science, and analyzes the mechanisms of telecom marker, then models and simulates them. This paper focuses on the following problems.1 According to the ACE object-oriented modeling approach, to lose customers refining system modeling process for the two sub-processes: One is the loss of customers from the true object-oriented systems of the conceptual model, which is the object-oriented analysis process. Another is the concept model to the computer simulation system, which is the object-oriented design process. In the design process, based on the simulation model design concept of the main attributes and methods, which is unique to this article.2 At existing theories (genetic algorithm, cellular automata and classification system) based on the customer and on the telecommunications operator behavior, interaction and association analysis. Then, in accordance with the Agent-based modeling methods (Swarm), and according to a complex system of Agent-based Distributed Simulation steps on customer satisfaction, it is done to model and simulate the telecommunications services and technical innovation of the Modeling and Simulation. The simulation will be built on the abstract level of customers, and operators of all kinds of transactions, and then the ultimate simulation results for comparative analysis.At last, the results are been explained and illuminated.
Keywords/Search Tags:telecom client prediction, client loyalty, swarm, modeling, simulation
PDF Full Text Request
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