1 |
Behavior of concrete under biaxial stresses
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[
Kupfer,H.;Hubert,K.;Hilsdorf,K.
] /
ACI Journal
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2 |
Knowledge-based modelling of material behavior with neural networks
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[
Ghaboussi,J.;Garrett,J.H.;Wu,X.
] /
Journal of Engineering Mechanics, ASCE
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3 |
Automatic early stopping using cross validation : quantifying the criteria
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[
Prechelt,L.
] /
Neural Networks
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4 |
A direct adaptive method for faster backpropagation learning: the RPROP algorithm
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[
Riedmiller,M.;Braun,H.
] /
Proceedings of the IEEE International Conference on Neural Networks
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5 |
Intelligent finite elements
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[
Shin,H.S.;Pande,G.N.;S.Valliappan(ed.);N.Khalili(ed.)
] /
Proceeding of Asian-Pacific Conference for Computational Mechanics(APVOM'01)
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6 |
/
[
Zienkiewicz,O.C.;Taylor,R.L.
] /
Finite element method (fifth edition)
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7 |
On the use of Neuronets for Simulating the Stress-Strain Behavior of Soils
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[
Najjar,Y.M.;Basheer,I.A.;Ali,H.E.;Pande,Pietruszczak(ed.)Schweiger,Rotterdam(ed.)
] /
Proceeding on Numerical Modes in Goemechanics-NUMOG VII
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8 |
Rate dependant behavior of clays using neural networks
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[
Penumadu,D.;Jin-Nan,K.L.;Chameau,J.L.;Arumugam,S.
] /
Proc. 13th Conference of Int. Soc. Soil Mechanics and Foundation Engineering
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9 |
Neural network based constitutive models for finite element analysis
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[
Shin,H.S.
] /
Ph.D thesis : C/Ph/250/01, Department of Civil Engineeing, University of Wales Suansea
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10 |
An elastoplastic constitutive model for concrete
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[
Pietruszczak,S.;Jiang,J.;Mirza,F.A.
] /
Int. J. Solid Structures
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11 |
On self-learning finite element codes based on monitored response of structures
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[
Shin,H.S.;Pande,G.N.
] /
Cpmputers and Geotechnics
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12 |
Enhancement of data for training neural network based constitutive models for geomaterials
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[
Shin,H.S.;Pande,G.N.;G.N.Pande(ed);S.Pietruszczak(ed)
] /
Proceeding of The Eighth International Symposium on Numerical Models in Geomechanics(NUMOG VIII)
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