Edited by: B.H.V. Topping
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Preliminaries |
I | KNOWLEDGE ENGINEERING |
1 |
A Product Model for Collaborative Building Design
I. Fahdah and W. Tizani |
2 |
The Establishment of a Knowledge Base for Building Construction Technology
H.C. Yang, Y.C. Shiau, S.W. Yeh, S.H. Yeh, S.M. Wang and J.Y. Tsai |
3 |
A Way of Creating a Personal Knowledge Accumulator
A.G. Razdolsky |
4 |
Human-Machine Interfaces for Structural Engineers in a Problem Solving Environment
H.K.M. van de Ruitenbeek and M.R. Beheshti |
II | GENETIC ALGORITHMS IN CIVIL AND STRUCTURAL ENGINEERING |
5 |
Enhancing the Search Space for Multiobjective Optimisation of Water Networks
L.S. Vamvakeridou-Lyroudia, D.A. Savic and G.A. Walters |
6 |
Optimal Restoration Scheduling under Uncertainty
H. Furuta, S. Hotta and K. Nakatsu |
7 |
Generation of Extended Uniform Latin Hypercube Designs of Experiments
V.V. Toropov, S.J. Bates and O.M. Querin |
III | SOFT COMPUTING TOOLS FOR STRUCTURAL OPTIMISATION |
8 |
A Simple Artificial Neural Network for Structural Re-Analysis in Planar Trusses
H.M. Gomes, A. Molter and P.A.M. Lopes |
9 |
Truss Topology Optimisation using Genetic Algorithms
T.J. McCarthy and A. Fenwick |
10 |
Optimum Geometry Design of Plane Trusses Supporting Distributed Loads using Genetic Algorithms
A. Maheri and M.R. Maheri |
11 |
Evolutionary Computing for Topology Optimization
T. Burczynski, A. Poteralski and M. Szczepanik |
12 |
Effects of Some Parameters in a Genetic Algorithm for Large Truss Structures
T. Dede, S. Bekiroglu and Y. Ayvaz |
13 |
Optimisation of Frames of a Milling Machine Tool using Genetic Algorithms and the Finite Element Method
P. Wilk and J. Kosmol |
14 |
Improving the Design of M-Shape Noise Barriers using the Boundary Element Method and Evolutionary Algorithms
D. Greiner, J.J. Aznárez, O. Maeso and G. Winter |
15 |
Optimizing the Collapse Behaviour of Tubes using Neural Networks and Genetic Algorithms
M. Shakeri and R. Mirzaeifar |
16 |
Optimum Design of Arch Dams using a Combination of Simultaneous Perturbation Stochastic Approximation and Genetic Algorithms
J. Salajegheh, E. Salajegheh, S.M. Seyedpoor and S. Gholizadeh |
IV | SOFT COMPUTING: DAMAGE, CONTROL AND SEISMIC ENGINEERING |
17 |
Analysis of a Model of Damage Condition to Light Structures using Clamping and Pruning Techniques
N.Y. Osman and K.J. McManus |
18 |
A Real Coded Genetic Algorithm for Fault Diagnosis on Structures
H.M. Gomes and N.R.S. Silva |
19 |
Damage Detection in Structures Based on Soft Computing and Wave Propagation
M. Orkisz and L. Ziemianski |
20 |
Optimisation of Structures for Earthquake Loads by a Self-Organizing Neural System
E. Salajegheh and S. Gholizadeh |
21 |
Estimating Fragility Curves of Buildings using Genetic Algorithms
F. Leon and G.M. Atanasiu |
22 |
Semi-Active Fuzzy Control of a MR Damper on Structures by Genetic Algorithm
Z.S. Huang, C. Wu and D.S. Hsu |
23 |
Seismic Vulnerability Evaluation of Geostructures using Efficient Neural Network Models
E.C. Georgopoulos, Y. Tsompanakis, N.D. Lagaros and P.N. Psarropoulos |
V | SOFT COMPUTING: GEOTECHNICAL ENGINEERING |
24 |
Prediction of Soil Compressibility using Nearest Neighbour Algorithms
I.E.G. Davey-Wilson |
VI | NEURAL NETWORKS: STRUCTURAL MECHANICS |
25 |
Analysis of Elasto-Plastic Plates using Artificial Neural Networks
S.T. Yousif and A.A. Abdul-Razzak |
26 |
A Neural Network Modelling of Steel Joint Block Shear Capacity
F. Rodrigues, L. Biondi Neto, P.C.G. da S. Vellasco, L.R.O. de Lima and M.M.B.R. Vellasco |
27 |
Production of Chloride Ingress Profile with Neural Networks in Concrete with Various PC-PFA-MK Binder Compositions
J. Bai and S. Wild |
28 |
Determination of the Bond-Slip Law for Reinforced and Prestressed Concrete using Computational Intelligence Techniques
E.T. Fonseca, M.E.N. Tavares, L.T. Menezes and I.S. Moura |
29 |
A Parametric Analysis of the Patch Load Behaviour using a Neuro-Fuzzy System
E.T. Fonseca, P.C.G. da S. Vellasco, S.A.L. de Andrade and M.M.B.R. Vellasco |
VII | NEURAL NETWORKS: CIVIL AND ENVIRONMENTAL ENGINEERING |
30 |
Application of Neural Networks for Wave Data Complement between Two Recording Stations
C.P. Tsai, H.B. Chen and C.P. Yang |
31 |
Using Neural Networks in the Selection of Optimal Equipment Combinations in Heavy Earth Moving Processes
E.M. Elkassas, M.A. Elganainy and H.H. Elammary |
VIII | NEURAL NETWORKS: MATERIALS MODELLING |
32 |
Application of Artificial Neural Networks for Pore Structure of High Strength Concrete
M.I. Khan |
33 |
Parallel Multi-Objective Identification of Material Parameters for Concrete
M. Leps |
34 |
Approximation of Constitutive Parameters for Material Models using Artificial Neural Networks
T. Most, G. Hofstetter, M. Hofmann, D. Novák and D. Lehký |
35 |
Lifetime Prediction with Neural Networks
S. Freitag, M. Beer, W. Graf and M. Kaliske |
36 |
Neural Networks as Material Models within a Multiscale Approach
J.F. Unger and C. Könke |
IX | ANT COLONY OPTIMISATION |
37 |
Resource-Constrained Scheduling using Ant Colony Optimization
S. Christodoulou |
38 |
Ant Colony Optimization of Reinforced Concrete Bridge Piers of Rectangular Hollow Section
F. Martinez, V. Yepes, A. Hospitaler and F. Gonzalez-Vidosa |
X | CELLULAR AUTOMATA |
39 |
Simulation of Evacuation Behaviours in a Subway Station using Cellular Automata
T. Madza, T. Goto and J. Arioka |
XI | DATA MINING |
40 |
Using Classification Rules to Develop a Predictive Indicator of Project Cost Overruns from Bidding Patterns
T.P Williams and W. Chaovalitwongse |
End matter / Index |