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| Preliminaries | 
| APPLIED SOFT COMPUTING IN STRUCTURAL ANALYSIS AND DESIGN ORGANISED BY D.C. CHARMPIS AND N.D. LAGAROS
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| 1 | Design of Experiments suitable for Sampling-Based Sensitivity Analysis A. Kucerová and E. Janouchová
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| 2 | Probabilistic Structural Analysis using Random Samples with Correlations induced by Simulated Annealing D.C. Charmpis
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| 3 | Robust Topology Optimization using Multi Objective Evolutionary Algorithms N.P. Garcia-Lopez, M. Sanchez-Silva, A.L. Medaglia and A. Chateauneuf
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| 4 | Optimum Seismic Design of Gravity Retaining Walls using the Heuristic Big Bang-Big Crunch Algorithm A. Kaveh, S. Talatahari and R. Sheikholeslami
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| 5 | Optimum Design of Reinforced Concrete Frames using a Heuristic Particle Swarm-Ant Colony Optimization A. Kaveh and O. Sabzi
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| 6 | Evolutionary Polynomial Regression as an Alternative Way to Predict the Torsional Strength of Reinforced Concrete Beams A. Fiore, L. Berardi, J. Avakian and G.C. Marano
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| 7 | The Impact of Soft Computing on Building Norms and Certification in Engineering M. Phiri
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| METAHEURISTIC OPTIMIZATION OF SKELETAL STRUCTURES ORGANISED BY O. HASANÇEBI AND L. LAMBERTI
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| 8 | Influence of Buckling Constraints on Reliability Based Multiobjective Design of Truss Structures D. Greiner and P. Hajela
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| 9 | Application of Evolution Strategy for Minimization of the Number of Modules in a Truss Branch Created with the Truss-Z System M. Zawidzki and K. Tateyama
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| 10 | Truss Structural Optimization using Hybrid Evolutionary Algorithms J.G. de Moura, G.F. Moita and S.R. de Souza
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| 11 | A Fast Big Bang-Big Crunch Optimization Algorithm for Weight Minimization of Truss Structures L. Lamberti and C. Pappalettere
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| 12 | A Reformulation of the Ant Colony Optimization Algorithm for Large Scale Structural Optimization O. Hasançebi, S. Çarbas and M.P. Saka
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| SOFT COMPUTING METHODS FOR ANALYSIS, OPTIMIZATION AND BAYESIAN UPDATING OF SYSTEMS UNDER UNCERTAINTY ORGANISED BY A.A. TAFLANIDIS AND C. PAPADIMITRIOU
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| 13 | Application of Soft Computing Techniques to Dam Safety Monitoring V. Rankovic, N. Grujovic, D. Divac, N. Milivojevic and G. Milanovic
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| 14 | Application of Response Surface Methodologies for Hurricane Risk Assessment A.A. Taflanidis
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| 15 | Relative Entropy Estimation through Stochastic Sampling and Stochastic Simulation Techniques G. Jia and A.A. Taflanidis
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| 16 | A Rough Set-Based Revised Counter-Propagation Network Model for Structural Damage Identification S.F. Jiang, C. Fu and J. Lin
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| 17 | Robust Optimization of Structural Risk: Coping with Epistemic Uncertainties A.T. Beck, W.J.S. Gomes and F.A.V. Bazán
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| HEURISTIC AND HYBRID METAHEURISTIC METHODS FOR STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING ORGANISED BY A. CSÉBFALVI
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| 18 | Optimal Design of Large-Span Shallow Dome Structures using the ANGEL Metaheuristic Method A. Csébfalvi and L. Mészáros
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| 19 | A Hybrid Metaheuristic for the Resource-Constrained Project Scheduling Problem with Fuzzy Activity Durations S. Danka
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| 20 | An Improved Hybrid Algorithm for the Resource-Constrained Project Scheduling Problem with Hammock Activities O. Eliezer and R. Levi
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| 21 | A Net Present Value Oriented Hybrid Method to Optimize the Revenue of Geothermal Systems with Respect to Operation and Expansion A. Csébfalvi and J. Pálné Schreiner
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| NEURAL COMPUTING | 
| 22 | Neural Stochastic Process Model Applied to Inflows Series L.C.D. Campos, M.M.B.R. Vellasco and J.G.L. Lazo
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| 23 | Settlement Prediction for Deep Foundation Piles using Artificial Neural Networks A. Abadkon and M.E. Akiner
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| 24 | A Two-Stage Neural Network Architecture for Forecasting River Flows M. Cisty
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| 25 | Bayesian Neural Networks Assessment of Stud Shear Connectors E.S. Goulart, P.C.G.S. Vellasco, R.R. de Araujo and M.M.B.R. Vellasco
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| 26 | Prediction of Tunnelling Induced Settlements using Simulation-Based Artificial Neural Networks J. Ninic, J. Stascheit and G. Meschke
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| 27 | Evaluation of Seismic Demand in Eccentric Setback Buildings: A Machine Learning Approach A. Emadi, A. Jahanmohammadi, H. Shakib and H. Moharrami
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| 28 | Recurrent Neural Networks for Fuzzy Data as a Material Description within the Finite Element Method S. Freitag, W. Graf and M. Kaliske
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| 29 | Deterioration Models for Australian Low Volume Traffic Roads using Neural Network Analysis K.J. McManus
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| 30 | Application of Artificial Neural Networks for Regional Flood Estimation in Australia: Formation of Regions Based on Catchment Attributes K. Aziz, A. Rahman, G. Fang and S. Shrestha
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| 31 | Analysis of Retractable Roof Structures S. Kmet and J. Cholvadt
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| SUPPORT VECTOR MACHINES | 
| 32 | Structural Damage Identification based on Nonlinear Feature Extraction of a Support Vector Machine S.F. Jiang, Z.Q. Wu and N. Yang
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| FUZZY INFERENCE SYSTEMS AND TOOLS | 
| 33 | Application of a Fuzzy Inference System to Patent Strategy Analysis of Fall Protection Technology W-D. Yu, S-T. Cheng, Y-H. Lai, C-C. Lin, C-M. Wu and S-S. Lou
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| INVERSE METHODOLOGIES | 
| 34 | Modelling the Structural Deformations of Tracheal Cartilage during Deep Dives C. Murphy, D. Kelliher and J. Davenport
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| CELLULAR AUTOMATA | 
| 35 | Stability Analysis of Multiple Vehicle Following Models Y. Wakita, H. Shimizu, T. Tamaki and E. Kita
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| PARTICLE SWARM OPTIMIZATION | 
| 36 | Reliability Based Optimal Design of Truss Structures using Binary Particle Swarm Optimization with Time-Varying Parameters C.K. Dimou and A.E. Charalampakis
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| 37 | Minimizing Thermal Residual Stresses in Ceramic Matrix Composites by using Particle Swarm Optimization Algorithm Y.J. Xu, W.H. Zhang, D. Chamoret and M. Domaszewski
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| GENETIC ALGORITHMS | 
| 38 | Introducing Full Memory in Genetic Algorithms A.E. Charalampakis
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| 39 | Optimal Polynomial Regression Models by using a Genetic Algorithm M. Hofwing, N. Strömberg and M. Tapankov
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| 40 | Optimal Removal of Heavy Metals Pollutants from Groundwater using a Real Genetic Algorithm A.R. Awad, I. Von Poser and M.T. Aboul-Ela
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| GENETIC ALGORITHMS: HYBRIDISATION | 
| 41 | Production Optimization of Petroleum Reservoirs using Hybrid Strategies L.C. Oliveira, S.M.B. Afonso and B. Horowitz
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| 42 | Hybrid Algorithms Based on Particle Swarm Optimization and the Powell Method for Global Optimization A.T. Beck and W.J.S. Gomes
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| GENETIC PROGRAMMING | 
| 43 | Control of Physical Consistency in Metamodel Building by Genetic Programming U. Armani, Z. Khatir, A. Khan, V.V. Toropov, A. Polynkin, H. Thompson, N. Kapur and C.J. Noakes
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| GENETIC OPERATION TREE | 
| 44 | Integration of Technology Evolution Trends and Genetic Operation Trees for the Generation of Innovative Alternatives C-M. Wu, W-D. Yu, S-T. Cheng and H-R. Lou
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| ANT COLONY OPTIMIZATION | 
| 45 | Two Pheromone Ant Colony Multiobjective Optimization to Design Dispersed Laminates for Structural Applications T.A. Sebaey, C.S. Lopes, N. Blanco and J. Costa
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| GRANULAR COMPUTING | 
| 46 | Resource Allocation in Infrastructure Networks through Clustering-Based Optimization C. Gómez, M. Sánchez-Silva and L. Dueñas-Osorio
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| DIFFERENTIAL EVOLUTION | 
| 47 | Pipe Network Design by Differential Evolution and Particle Swarm Optimization M. Cisty, Z. Bajtek and J. Bezak
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| 48 | A Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithms for the Identification of Bouc-Wen Hysteretic Systems A.E. Charalampakis and C.K. Dimou
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| 49 | Normalized Dominance Selection Criteria for Differential Evolution Algorithms in Constrained Optimization Problems J. Avakian, D. Serio, A. Giannico and G.C. Marano
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| KRIGING APPROXIMATION | 
| 50 | Fast Multilevel Optimization using a Multiparametric Strategy and a Cokriging Metamodel L. Laurent, P.A. Boucard and B. Soulier
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| ENTROPY MAXIMIZATION | 
| 51 | An Entropy-Based Primer for Traffic Management and Bus Routing Optimization S.E. Christodoulou
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| DATA MINING | 
| 52 | Data Mining Techniques for the Assessment of Factors Contributing to the Damage of Residential Houses in Australia N.Y. Osman-Schlegel, Z.A. Krezel and K.J. McManus
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| 53 | Application of Data Mining in a Global Optimization Algorithm T.Y. Chen and J.H. Huang
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| End matter / Index |