Title :
Bridge Deterioration Diagnostic System Based on Neural Network Considering Peripheral Environmental Conditions
Author :
Ken-ichiro, SATO ; Hideyuki, Takashima
Author_Institution :
Dept. of Archit., Kanto Gakuin Univ., Yokohama, Japan
fDate :
March 31 2009-April 2 2009
Abstract :
In order to establish the bridge deterioration diagnostic system, this paper argues about the data visualization and how to create neural network as the reasoning engine to predict the deterioration. The visualization system has been almost completed at the present stage, and it explains the details. In addition, the availability of AIC on establishing the neural network has also been discussed. As conclusions, several targets are introduced to complete developing the present system.
Keywords :
bridges (structures); condition monitoring; data visualisation; neural nets; structural engineering computing; bridge deterioration diagnostic system; data visualization; neural network; peripheral environmental condition; Bridges; Data engineering; Data visualization; Engines; Humidity; Neural networks; Rivers; Snow; Visual databases; Wind speed; AIC; deterioration diagnostic system; neural network; peripheral environment; reasoning engine;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.1009
