The door of novel computing paradigm called Soft Computing (SC) was opened by Zadeh in 1990s, where SC is a consortium of methodologies, combines different well-known artificial intelligence methods that work synergistically and provides, in one form or other, flexible information processing capability of handling real life ambiguous situations. According to Zadeh (1994): “……in contrast to traditional, had computing, soft computing is tolerant of imprecision, uncertainty, and partial truth.”


In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost.

At this juncture, the principal constituents of soft computing (SC) are fuzzy logic (FL), neural network theory (NN), Genetic Algorithms (GA) and probabilistic reasoning (PR), with the latter subsuming belief networks, chaos theory and parts of learning theory. What is important to note is that SC is not a mélange of FL, NN, GA and PR. Rather; it is a partnership in which each of the partners contributes a distinct methodology for addressing problems in its domain. In this perspective, the principal contributions of FL, NN, GA and PR are complementary rather than competitive.


Among these existing soft-computing tools, neural networks, fuzzy logic and genetic algorithms have shown potential in their application to civil engineering field. 


The main objective of the research activities in our group is to address following issues:


·          Explore Soft Computing (SC) tools applications in civil engineering domain

·          Develop hybrid soft computing Tools for applications

·          Fusion of soft computing and hard computing

·          Incorporate advances in computing paradigm into civil engineering domain


© 2010 Sudhirkumar Barai