A study on generalized neural network system for recognizing nonlinear behaviour of structures

T. Mazda, H. Otsuka, W. Yabuki, M. Tsuruta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multiple layered neural network to simulate the non-linear hysteretic behavior like Ramberg-Osgood model, modified bilinear model and Takeda model is described. Based on the pattern recognition ability of neural network, non-linear hysteretic behavior is modeled by the network directly without replacing it with a mathematical model. Thus, the effectiveness and applicability of the network in numerical analysis are evaluated. It is found that neural network transmits the signals from the input layer to the output layer by way of the hidden layers when the input signals is received, and output layer by way o the hidden layers when the input signals is received, and output the output signals finally.

Original languageEnglish
Title of host publicationProceedings of the Third International Conference on Engineering Computational Technology
EditorsB.H.V. Topping, Z. Bittnar, B.H.V. Topping, Z. Bittnar
Pages209-210
Number of pages2
Publication statusPublished - Dec 1 2002
EventProceedings of the Third International Conference on Engineering Computational Technology - Prague, Czech Republic
Duration: Sep 4 2002Sep 6 2002

Publication series

NameProceedings of the Third International Conference on Engineering Computational Technology

Other

OtherProceedings of the Third International Conference on Engineering Computational Technology
CountryCzech Republic
CityPrague
Period9/4/029/6/02

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'A study on generalized neural network system for recognizing nonlinear behaviour of structures'. Together they form a unique fingerprint.

  • Cite this

    Mazda, T., Otsuka, H., Yabuki, W., & Tsuruta, M. (2002). A study on generalized neural network system for recognizing nonlinear behaviour of structures. In B. H. V. Topping, Z. Bittnar, B. H. V. Topping, & Z. Bittnar (Eds.), Proceedings of the Third International Conference on Engineering Computational Technology (pp. 209-210). (Proceedings of the Third International Conference on Engineering Computational Technology).