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19  Articles
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The number of users and their network utilization will enumerate the traffic of the network. The accurate and timely estimation of network traffic is increasingly becoming important in achieving guaranteed Quality of Service (QoS) in a wireless network. T... see more

The actual problem of modeling of the multivariate nonstationary time series of economic dynamics is being researched for the purpose of analysis, forecasting and decision-making in financial markets.The proposed approach to the modeling of time series is... see more

A concept of a decision support system (DSS) for modeling and forecasting of economic and financial processes is proposed as well as its software implementation. The main functions of the DSS are in modeling and short-term forecasting of nonstationary non... see more

In this paper, we investigate the nonlinearity and nonstationarity of Turkish output series applying a Markov regime switching augmented Dickey Fuller unit root test. We document that the output series are characterized by a two-regime Markov switching un... see more

Context. Nonlinear nonstationary processes are observed today in various fields of studies: economy, finances, ecology, demographyetc. Very often special approaches are required for model development and forecasts estimation for the processes mentioned.Th... see more

AbstractIn this article we fit a time-dependent generalised extreme value (GEV) distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six... see more

To construct an online kernel adaptive filter in a non-stationary environment, we propose a randomized feature networks-based kernel least mean square (KLMS-RFN) algorithm. In contrast to the Gaussian kernel, which implicitly maps the input to an infinite... see more

Long-term hydro-climatic datasets and sophisticated change detection methods are essential for estimating hydro-climatic trends at regional and global scales. Here, we use the ensemble empirical mode decomposition method (EEMD) to investigate runoff oscil... see more

At present, manual observation of the electroencephalogram (EEG) signals is the prime method for diagnosis of epileptic seizure disorders. The method is a time consuming and error prone as it involves errors due to fatigue in continuous monitoring of nonl... see more

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