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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 3/2017

18.11.2015 | Original Article

Fuzzy neural network-based system identification of multi-storey shear buildings

verfasst von: S. Chakraverty, Deepti Moyi Sahoo

Erschienen in: Neural Computing and Applications | Ausgabe 3/2017

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Abstract

This paper uses fuzzy neural network modelling for the identification of structural parameters of multi-storey shear buildings. First the identification has been done using response of the structure subject to ambient vibration with fuzzy initial condition. Then forced vibration with horizontal displacement in fuzzified form has been used to investigate the identification procedure. The model has been developed to handle the data in fuzzified form for multi-storey shear structure, and the procedure is tested for the identification of the stiffness parameters of simple example problems using the prior values of the design parameters.
Vorheriger Artikel Extension of Laplace transform–homotopy perturbation method to solve nonlinear differential equations with variable coefficients defined with Robin boundary conditions
Nächster Artikel Rule-based back propagation neural networks for various precision rough set presented KANSEI knowledge prediction: a case study on shoe product form features extraction

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Metadaten
Titel
Fuzzy neural network-based system identification of multi-storey shear buildings
verfasst von
S. Chakraverty
Deepti Moyi Sahoo
Publikationsdatum
18.11.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 3/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-2101-y

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