telephone traffic metering device

2011 ◽  
Keyword(s):  
Traffic Metering ◽  
Telephone Traffic

Research on Combined Prediction Model for Busy Telephone Traffic

2014 ◽  
Vol 610 ◽  
pp. 789-796
Author(s):  
Jiang Bao Li ◽  
Zhen Hong Jia ◽  
Xi Zhong Qin ◽  
Lei Sheng ◽  
Li Chen
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Prediction Method ◽  
Pso Algorithm ◽  
Frequency Component ◽  
Least Square ◽  
High Frequency Component ◽  
Support Vector ◽  
Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

New Method Research on Prediction Model for Busy Telephone Traffic

2013 ◽  
Vol 12 (16) ◽  
pp. 3619-3625
Author(s):  
Li Jiang-Bao ◽  
Jia Zhen-Hong ◽  
Qin xi-Zhong ◽  
Sheng Lei ◽  
Chen Li
Keyword(s):  
Prediction Model ◽  
New Method ◽  
Telephone Traffic

Introductory remarks

1990 ◽  
Vol 332 (1627) ◽  
pp. 417-418
Keyword(s):  
Probability Theory ◽  
Brownian Motion ◽  
Random Walk ◽  
Stochastic Processes ◽  
Statistical Physics ◽  
Late 19Th Century ◽  
Fields Of Study ◽  
Wide Range ◽  
Influential Paper ◽  
Telephone Traffic

Stochastic processes are systems that evolve in time probabilistically; their study is the ‘dynamics’ of probability theory as contrasted with rather more traditional ‘static’ problems. The analysis of stochastic processes has as one of its main origins late 19th century statistical physics leading in particular to studies of random walk and brownian motion (Rayleigh 1880; Einstein 1906) and via them to the very influential paper of Chandrasekhar (1943). Other strands emerge from the work of Erlang (1909) on congestion in telephone traffic and from the investigations of the early mathematical epidemiologists and actuarial scientists. There is by now a massive general theory and a wide range of special processes arising from applications in many fields of study, including those mentioned above. A relatively small part of the above work concerns techniques for the analysis of empirical data arising from such systems.

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