Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 6370

Moving total least squares for parameter identification in mathematical model


Scitovski, Rudolf; Ungar, Šime; Jukić, Dragan; Crnjac, Miljenko
Moving total least squares for parameter identification in mathematical model // Operations Research Proceedings / Kleinschmidt, P. ; Bachem, A. ; Leopold-Wildburger, U. et al. (ur.).
Berlin: Springer-Verlag, 1996. str. 196-201 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 6370 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Moving total least squares for parameter identification in mathematical model

Autori
Scitovski, Rudolf ; Ungar, Šime ; Jukić, Dragan ; Crnjac, Miljenko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Operations Research Proceedings / Kleinschmidt, P. ; Bachem, A. ; Leopold-Wildburger, U. et al. - Berlin : Springer-Verlag, 1996, 196-201

Skup
Symposium on Operations Research

Mjesto i datum
Passau, Njemačka, 13.09.1995. - 15.09.1995

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
surface generating; moving least squares; smoothing

Sažetak
We consider a parameter identification problem in a mathematical model which is described by a system of differential equations, Usually it is not possible to expres s the solution of such a system by means of elementary functions, but nevertheless, one has to estimate the optimal parameter values using the experimental data. In our paper we apply the smooth-the-data method. In order to obtain smooth function we are using the moving total least squares method (TLS). The local approximants are linear functions obtained by applying the TLS method usin appropriate weight functions. This means that for each local approximant one has to find the smallest singular value for a second order matrix. The reason for using the TLS is the fact that the reeors may be expected in experimental measurements of both the independent and the dependent variables in the model. Once the optimal parameters are estimated, the ooptimal initial conditions are going to be estimated using the quasilinearisation method. The method is going to be tested on the mathematical model of insulin sensitivity.

Izvorni jezik
Engleski

Znanstvena područja
Matematika



POVEZANOST RADA


Projekti:
165021
037006

Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Šime Ungar (autor)

Avatar Url Miljenko Crnjac (autor)

Avatar Url Rudolf Scitovski (autor)

Avatar Url Dragan Jukić (autor)


Citiraj ovu publikaciju:

Scitovski, Rudolf; Ungar, Šime; Jukić, Dragan; Crnjac, Miljenko
Moving total least squares for parameter identification in mathematical model // Operations Research Proceedings / Kleinschmidt, P. ; Bachem, A. ; Leopold-Wildburger, U. et al. (ur.).
Berlin: Springer-Verlag, 1996. str. 196-201 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Scitovski, R., Ungar, Š., Jukić, D. & Crnjac, M. (1996) Moving total least squares for parameter identification in mathematical model. U: Kleinschmidt, P., Bachem, A. & Leopold-Wildburger, U. (ur.)Operations Research Proceedings.
@article{article, author = {Scitovski, Rudolf and Ungar, \v{S}ime and Juki\'{c}, Dragan and Crnjac, Miljenko}, year = {1996}, pages = {196-201}, keywords = {surface generating, moving least squares, smoothing}, title = {Moving total least squares for parameter identification in mathematical model}, keyword = {surface generating, moving least squares, smoothing}, publisher = {Springer-Verlag}, publisherplace = {Passau, Njema\v{c}ka} }
@article{article, author = {Scitovski, Rudolf and Ungar, \v{S}ime and Juki\'{c}, Dragan and Crnjac, Miljenko}, year = {1996}, pages = {196-201}, keywords = {surface generating, moving least squares, smoothing}, title = {Moving total least squares for parameter identification in mathematical model}, keyword = {surface generating, moving least squares, smoothing}, publisher = {Springer-Verlag}, publisherplace = {Passau, Njema\v{c}ka} }




Contrast
Increase Font
Decrease Font
Dyslexic Font