9402049 Chou The neural network's capability of making reasonable response (output) even when it was presented with incomplete, noisy or previously unseen input has significant impact in engineering applications. Many times, due to physical or environmental limitations such as after a natural disaster, not all forms or types of data are collected for safety analysis. In this situation, tradition reliability analysis could be halted, terminated or greatly compromised. In addition, neural network accepts relationships between input and response that are deterministic, probabilistic or fuzzy. The Career Advancement Award for Women Scientists and Engineers provides the Investigator an opportunity to expand her current research area of structural safety utilizing probabilistic, statistical and fuzzy set theory to civil engineering, particularly structural engineering. Neural network is an artificial intelligence tool that has shown to be more flexible than expert systems. From studies performed in other engineering disciplines, they show great potential that the concept is applicable to civil engineering problems as well. ***

Project Start
Project End
Budget Start
1994-08-15
Budget End
1996-07-31
Support Year
Fiscal Year
1994
Total Cost
$49,938
Indirect Cost
Name
University of Tennessee Knoxville
Department
Type
DUNS #
City
Knoxville
State
TN
Country
United States
Zip Code
37996