Techno Press
You logged in as Techno Press

Structural Engineering and Mechanics
  Volume 6, Number 8, December 1998 , pages 955-969

Soft computing with neural networks for engineering applications: Fundamental issues and adaptive approaches
Jamshid Ghaboussi and Xiping Wu

    Engineering problems are inherently imprecision tolerant. Biologically inspired soft computing methods are emerging as ideal tools for constructing intelligent engineering systems which employ approximate reasoning and exhibit imprecision tolerance. They also offer built-in mechanisms for dealing with uncertainty. The fundamental issues associated with engineering applications of the emerging soft computing methods are discussed, with emphasis on neural networks. A formalism for neural network representation is presented and recent developments on adaptive modeling of neural networks, specifically nested adaptive neural networks for constitutive modeling are discussed.
Key Words
    neural networks, soft computing, computational mechanics, constitutive models.
Ghaboussi J, Univ Illinois, Dept Civil Engn, Urbana, IL 61801 USA
Univ Illinois, Dept Civil Engn, Urbana, IL 61801 USA
Exxon Prod Res Co, Offshore Div, Houston, TX 77252 USA

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2023 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: