Predictive and Comparative Analysis of NARX and NIO Time Series Prediction
Journal Title: American journal of Engineering Research - Year 2017, Vol 6, Issue 9
Abstract
Telecommunication is one of the most unavoidable utilities of daily life of human being. It provides data records of its services from call logs, port activities to internet usage or consumption. This paper investigates and explored the methodologies for modeling, simulation and controls in ANN based of time series application of telecommunication. To show and prove efficiency, simulated and operational data sets are employed to demonstrate the capability of neural networks in capturing complex nonlinear dynamics where NARX and NIO models are set up to explore and compare both steady-state and transient features on daily internet usage activities. The structures were configured, generated and run in MATLAB to create and train platform, validation, testing and results demonstrate that the techniques can be applied accurately which means that both models successfully capture dynamics of the system up to a certain degree of acceptance. The related parameters for the design and simulation are tuned and set up according to the requirements which show that ANN can perform even better than conventional methods. Finally, it was deduced that NARX model outperform more than the NIO model.
Authors and Affiliations
Omolaye O. Philip1 ;, Badmos T. Adeleke
Keywords
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