In Bierens (1987) a Granger causal relation was found between unemployment and the interest rate for the Netherlands. In the present paper we will investigate whether there exists a simüar Granger causal relation between unemployment and interest rate for a number of other countries. It appears that, with our ARMAX modeling approach, this relationship is not confined to the Netherlands, but als...

This paper presents a unified framework for the analysis of several discrete time adaptive parameter estimation algorithms, including RML with nonvanishing stepsize, several ARMAX identifiers, the Landau-style output error algorithms, and certain others for which no stability proof has yet appeared. A general algorithmic form is defined, incorporating a linear time-varying regressor '. filter a...

This paper focuses on a comparative study of a new estimation method applied on a wireless sensor network, installed in a closed space container. We would like to pick out the best method among the existing identification methods such as ARX, ARMAX, OE, BJ and SS. we are looking for a way to reduce power consumption due to measuring and transmitting data in some desired sensor nodes (DSNs) and ...

Accurate forecasting of future performance of hotels is needed so hospitality constituencies in specific destinations can benchmark their properties and better optimize operations. As competition increases, hotel managers have urgent need for accurate short-term forecasts. In this study, time series models including several tourism big data sources, including search engine queries, website traf...

This paper presents an improved on-line identification method of non-linear time-varying dynamic systems with linear and non-linear models . This method is based on Genetic algorithms with a new technique to simulate the behaviour of the gradient method without using the concept of derivatives. This method uses an on-line identification algorithm that begins by calculating what ARX model adapts...

This paper develops a new methodology for identifying the structure of VARMA time series models. The analysis proceeds by examining the echelon canonical form and presents a fully automatic data driven approach to model specification using a new technique to determine the Kronecker invariants. A novel feature of the inferential procedures developed here is that they work in terms of a canonical...

We present a novel application of deep learning in networking. The envisioned system can learn the original flow characteristics such as a burst size and inter-burst gaps conceived at the source from packet sampling done at a receiver Wi-Fi node. This problem is challenging because CSMA introduces complex, irregular alterations to the origin pattern of the flow in the presence of competing flow...

This report surveys time series methods that have been used and can be applied in predicting end-to-end delay of the Internet. ARIMA scheme and state-space approach are discussed and compared. Although state-space approach has the advantages in structure and computation, ARIMA modeling is still useful in identifying systems due to the complexity and uncertainty of the Internet. A practical exam...

This paper aims to describe a comparative study regarding several identification models and control solutions for an active suspension system, while corrupted by narrow band disturbances. The tested identification models are linear and belong to ARMAX class. Several identification methods were compared in terms of disturbances rejection, both in open and closed loop cases. Beside the Least Squa...