With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels.
Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations.
Topics include

Neural networks

Genetic algorithms

Numerical modeling

Fuzzy sets and operations

Reliability and risk analysis

Systems control

Uncertainty in probability estimates
This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.

Contributions by: Jamshid Mohammadi, Peggy A. Johnson, Lucien Duckstein, Gregory B. Baecher, Dong Boru, Daniel Bruchman, Claudio Carino, Gang-Len Chang, Yun-His Oscar Chang