In a wireless network environment accurate and timely estimation or prediction of network traffic has gained much importance in the recent past. The network applications use traffic prediction results to maintain its performance by adopting its behaviors. Network Service provider will use the prediction values in ensuring the better Quality of Service(QoS) to the network users by admission cont...

There has been increased interest in time series data mining recently. In some cases, approaches of real-time segmenting time series are necessary in time series similarity search and data mining, and this is the focus of this paper. A real-time iterative algorithm that is based on time series prediction is proposed in this paper. Proposed algorithm consists of three modular steps. (1) Modeling...

A crucial problem in non-linear time series forecasting is to determine its auto-regressive order, in particular when the prediction method is non-linear. We show in this paper that this problem is related to the fractal dimension of the time series, and suggest using the Curvilinear Component Analysis (CCA) to project the data in a non-linear way on a space of adequately chosen dimension, befo...

Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify estimate long parameter partially integrated series. One common models used represent that a ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are fractional number called parameter. To analyze determine model, fractal must be...

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is suffic...

Simulated models suffer intrinsically from validation and comparison problems. The choice of a suitable indicator quantifying the distance between the model and the data is pivotal to model selection. However, how to validate and discriminate between alternative models is still an open problem calling for further investigation, especially in light of the increasing use of simulations in social ...