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Title:Neural Network Material Models Determined From Structural Tests
Author(s):Zhang, Mingfu Michael
Doctoral Committee Chair(s):Ghaboussi, J.; D. Pecknold
Department / Program:Civil Engineering
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Artificial Intelligence
Abstract:A nested modular neural network structure is introduced in this study and applied to model uniaxial concrete behavior under cyclic loading and biaxial concrete behavior under monotonic loading and unloading. The results show that the nested modular neural network structure is more flexible and efficient to model path-dependent material behavior than the fully-connected internal neural network structure.
Issue Date:1997
Type:Text
Language:English
Description:157 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.
URI:http://hdl.handle.net/2142/83429
Other Identifier(s):(MiAaPQ)AAI9717351
Date Available in IDEALS:2015-09-25
Date Deposited:1997


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