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- W2954931872 abstract "A network traffic prediction model is built based on LSTM neural network optimized with the improved firefly algorithm (IFA-LSTM). Aiming at some disadvantages of firefly algorithm including slow convergence, and easy to fall in local optimal values, we introduce a location update strategy based on the diversity of population, to avoid the optimization to fall into local optimal values. A dynamic step length updating measure is proposed to improve accuracy of the optimization, and to avoid the optimal solutions’ oscillation problem. Simulation examples show that the prediction accuracy and convergent speed of the IFA-LSTM method are obviously improved,it can be used to predict network traffic." @default.
- W2954931872 created "2019-07-12" @default.
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- W2954931872 date "2019-04-13" @default.
- W2954931872 modified "2023-09-24" @default.
- W2954931872 title "Network Traffic Forecasting Using IFA-LSTM" @default.
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- W2954931872 doi "https://doi.org/10.1007/978-3-030-14680-1_75" @default.
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