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

Volume

4

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

153

Lastpage

157

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.1009

Filename

5170978