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Barai@Soft.Computing.Activities |
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Background |
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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 |
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© 2010 Sudhirkumar Barai |
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