SHORT-TERM PREDICTION OF TRAFFIC RATE INTERVAL ROUTER USING DYNAMIC SYNAPSE NEURAL NETWORK

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SHAKIBA MARYAM; TESHNEHLAB M.; ZOKAIE S.

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Journal Paper

Paper Information

Journal: Majlesi Journal of Electrical Engineering Year:2009 | Volume:3 | Issue:2 (9) Page(s): 1-5

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Title

SHORT-TERM PREDICTION OF TRAFFIC RATE INTERVAL ROUTER USING DYNAMIC SYNAPSE NEURAL NETWORK

Author(s)

SHAKIBA MARYAM | TESHNEHLAB M. | ZOKAIE S. | Issue Writer Certificate

Keywords

PREDICTION OF TIME SERIESQ3

TIME DELAY LINE NEURAL NETWORKQ3

DYNAMIC SYNAPSE NEURAL NETWORK AND PSO ALGORITHMQ3

Abstract

Prediction is an important issue in many dynamical systems and is vital for effective management and control of plants. An important process which has recently derived much attention is the congestion control problem. Prediction of different traffic parameters can help in managing a congestion in a computer network. In this thesis, using real data for from the router between Iran Telecommunication Research Center and data Data company during December, January, February and March 2007, the router interval traffic rates are analyzed. Also, a comparative study is performed using the different methods employed and prediction results are provided to show the effectiveness of the predictions.

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APA: Copy

SHAKIBA, MARYAM, TESHNEHLAB, M., & ZOKAIE, S.. (2009). SHORT-TERM PREDICTION OF TRAFFIC RATE INTERVAL ROUTER USING DYNAMIC SYNAPSE NEURAL NETWORK. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 3(2 (9)), 1-5. SID. https://sid.ir/paper/188253/en

Vancouver: Copy

SHAKIBA MARYAM, TESHNEHLAB M., ZOKAIE S.. SHORT-TERM PREDICTION OF TRAFFIC RATE INTERVAL ROUTER USING DYNAMIC SYNAPSE NEURAL NETWORK. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2009;3(2 (9)):1-5. Available from: https://sid.ir/paper/188253/en

IEEE: Copy

MARYAM SHAKIBA, M. TESHNEHLAB, and S. ZOKAIE, “SHORT-TERM PREDICTION OF TRAFFIC RATE INTERVAL ROUTER USING DYNAMIC SYNAPSE NEURAL NETWORK,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 3, no. 2 (9), pp. 1–5, 2009, [Online]. Available: https://sid.ir/paper/188253/en

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