world of soft computing provides powerful tools for civil engineers to carry
out various numerical simulation studies. Some of them are knowledge driven
methods, such as Fuzzy Logic and
Probabilistic Reasoning approaches.
Others are data driven methods, like Artificial
Neural Networks and Evolutionary Computing approaches. These methods independently, and in hybrid forms, have been
successfully applied in the following various fields of civil engineering.
- Structural analysis, design, diagnostics and control problems, Structural
health monitoring, Structural material behavior modeling etc.
engineering - Flood forecasting,
Flood routing model, Hydrology etc.
engineering - Air quality prediction,
Water quality prediction model etc.
engineering- Liquefaction potential assessment, piles design, etc.
engineering - Bridge management systems, Pavement management systems, Pavement behavior models etc.
Systems (GIS), Global Positioning Systems, Remote Sensing etc.
Automation- Automated inspection, Risk analysis and decision making, Supply
chain management, Construction process reengineering, Procurement management,
Environment management, and Safety management etc.
Selected Papers For Oral
Infiltration Parameters using Artificial Neural Networks
Ashu Jain1 and
1Assistant Professor, Department of Civil Engineering, Indian Institute
of Technology Kanpur – 208 016; (0512) 259 7411(O)/7395(Fax); firstname.lastname@example.org
2Ex-Post Graduate Student; Department of Civil Engineering,
Indian Institute of Technology Kanpur – 208 016; email@example.com
Decision Making in Water Resources
K. Srinivasa Raju1, D. Nagesh Kumar2
1 Civil Engineering Department, Birla Institute of Technology and
Science, Pilani 333 031
2 Civil Engineering Department, Indian Institute of Science,
Bangalore 560 012
Theoretical aspects of artificial neural network
based vehicular exhaust emission modeling
S.M. Shiva Nagendra and Mukesh Khare*
Department of Civil Engineering,
Indian Institute of
Technology Delhi, Hauz Khas,
New Delhi – 11 00 016,
Hybrid Learning Model for
Liquefaction Potential Assessment
S V Barai 1, and Gaurav Agarawal 2
1 Assistant Professor, Department of Civil Engineering, Indian
Institute of Technology Kharagpur 721 302, India
IBM Global Services India,
"Prestige Towers", 3rd Floor, 'A' Wing #38A,
No.99, Residency Road, Bangalore-560025, India
ANN Application in End
Depth Computation for Inverted Semicircular Channels
Raikar R V
Doctoral Research Fellow
Dept. of Civil Engineering,
Indian Institute of Technology, Kharagpur 721302, West Bengal, India
Tel: +91 3222 283418; Fax:
+91 3222 282254;
Accident Rate Prediction
on Rural Highways Using Artificial
Ramachandra Rao Kalaga1,
Venkata Narasimham Kannekanti2
1 Department of Civil Engineering, Indian Institute of
Technology Delhi, Hauz Khas,
New Delhi 110 016, India
2 Department of Civil and Environmental Engineering,
University of California Davis,
California 95616, USA
Comparative Analysis of
Back-Propagation and Real-Coded GA for Training of ANN
1PhD Student, Department of Civil Engineering, IIT Kanpur,
2Assistant Professor, Department of Civil Engineering, IIT
Kanpur, India; firstname.lastname@example.org
Neural Network-Based Estimation Of Stress
Concentration Factors For Steel Multiplanar Tubular XX-Joints
Ashok Gupta2 and S. P. Chiew3
Facility Location using Multi-Objective Genetic Algorithms
T. Devi Prasad*, Godfrey A.
Walters, and Dragan A. Savic
School of Engineering, University of Exeter, Exeter – EX4