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Recently, the Float Car technology is playing a more and more important role in real-time traffic service systems because it can collect real-time traffic information with low cost, high coverage and high efficiency. Meanwhile, the ability to accurately predict travel times in transportation networks is becoming a critical component for many Intelligent Transportation Systems. This paper focuses on...
Modeling of real world financial time series such as stock returns are very difficult, because of their inherent characteristics. ARIMA and GARCH models are frequently used in such cases. It is proven of late that, the traditional models may not produce the best results. Lot of recent literature says the successes of hybrid models. The modeling and forecasting ability of ARFIMA-FIGARCH model is investigated...
The paper describes methods of comparing calculated ECG signal with real signal. Five examination methods of ECG-signal reconstruction from reduced system were proposed in this description. These methods prove reconstruction and evaluate results. They are based on statistic methods, nonparametric approaches and autoregressive models.
With the continuous deterioration of the network environment, a variety of viruses, Trojans continue to affect the security of the network. Through the network traffic anomaly detection and analysis can efficiently find problems existing in the network. This paper discusses the network traffic flow data predict and network anomaly detection, network traffic prediction using ARMA model, network anomaly...
Traffic prediction constitutes a hot research topic of network metrology. Thus, tuning the prediction model parameters is very crucial to achieve accurate prediction. This work focuses on the design, the empirical evaluation and the analysis of the behavior of linear models for predicting the throughput of a single link. In this work, the autoregressive integrated moving average (ARIMA) model and...
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