Abstract
The traffic prediction are mainly used to improve the performance of telecommunication network management. This paper improved model for telephone traffic prediction in Thailand by using artificial neural network (ANN) with back propagation learning algorithms. By applied data which is collected at different node in main routes of TOT, Thailand telephone network for learning process and testing. The neural network structure and input/output musters are descried in detail. We present the comparatively results of simulation with another methods, the results shows traffic fluctuation prediction by the method of ANN is accurately.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
