Temat: NARMAX system - Prolib Integro

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Tytuł:: Nonparametric instrumental variables for identification of block-oriented systems
Autorzy:: Mzyk, G.
Tematy:: system identification
instrumental variables
NARMAX system
Hammerstein system
Wiener system
Lur'e system
nonparametric method
identyfikacja systemu
zmienna instrumentalna
system Hammersteina
system Wienera
metoda nieparametryczna; Pokaż więcej
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Powiązania:: https://bibliotekanauki.pl/articles/330283.pdf Link otwiera się w nowym oknie
Opis:: A combined, parametric-nonparametric identification algorithm for a special case of NARMAX systems is proposed. The parameters of individual blocks are aggregated in one matrix (including mixed products of parameters). The matrix is estimated by an instrumental variables technique with the instruments generated by a nonparametric kernel method. Finally, the result is decomposed to obtain parameters of the system elements. The consistency of the proposed estimate is proved and the rate of convergence is analyzed. Also, the form of optimal instrumental variables is established and the method of their approximate generation is proposed. The idea of nonparametric generation of instrumental variables guarantees that the I.V. estimate is well defined, improves the behaviour of the least-squares method and allows reducing the estimation error. The method is simple in implementation and robust to the correlated noise.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Predicting the Atlantic Meridional Overturning Circulation Using Nonlinear System Identification Methods and the NARMAX Model
Przewidywanie atlantyckiej południkowej cyrkulacji z wykorzystaniem nieliniowych metod identyfikacji systemu i modelu NARMAX
Autorzy:: Weil, Hua-Liang
Bigg, Grant R.
Hanna, Edward
Tematy:: atlantic meridional overturning circulation
north atlantic oscillation
nonlinear system identification methods
narmax model
Atlantycka Południkowa Cyrkulacja Wymienna
oscylacja północnoatlantycka
metody identyfikacji systemów nieliniowych
model NARMAX; Pokaż więcej
Wydawca:: Polskie Towarzystwo Przeróbki Kopalin
Powiązania:: https://bibliotekanauki.pl/articles/59114940.pdf Link otwiera się w nowym oknie
Opis:: The Atlantic Meridional Overturning Circulation (AMOC) plays an important role in the coupled ocean-climate system and in global climate change. The analysis of its own behaviour and the understanding its links to other climate dynamics is of paramount importance today as we encounter an increasing pressure to adapt to climate change. Due to the enormous complexity, it is almost impossible to establish accurate models, purely based on firstprinciple modelling approaches, that can perfectly represent the relationships between the AMOC and other dynamic climate parameters. Data-based or data-driven modelling methods, can therefore provide an attractive alternative solution. Systematic regular and continuous measurement of the AMOC time series began in April 2004. The main objective of the paper is to use the monthly data of the AMOC measured during April 2004-Febuary 2017, together with the North Atlantic Oscillation (NAO) index, and density anomalies of the Gulf of Mexico, Labrador Sea and Norwegian Sea, measured during the same period, to investigate and understand the quantitative relationship between the AMOC and four drivers (NAO and the three density anomaly variables). In doing so, nonlinear system identification methods and the Nonlinear AutoRegressive Moving Average with Exogenous input (NARMAX) method are employed to develop a quantitative model that relates the AMOC to the four drivers. Experimental results show that the derived nonlinear model skillfully captures and represents the dynamics of the AMOC based on the other four variables. One of the findings from this study is that the use of autoregressive variables can help improve the prediction of the AMOC.
Dostawca treści:: Biblioteka Nauki

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