Name
Title | ||
|---|---|---|
Multiresolution classification with semi-supervised learning for indirect bridge structural health monitoring |
Abstract | ||
|---|---|---|
We present a multiresolution classification framework with semi-supervised learning for the indirect structural health monitoring of bridges. The monitoring approach envisions a sensing system embedded into a moving vehicle traveling across the bridge of interest to measure the modal characteristics of the bridge. To enhance the reliability of the sensing system, we use a semi-supervised learning algorithm and a semi-supervised weighting algorithm within a multiresolution classification framework. We show that the proposed algorithm performs significantly better than supervised multiresolution classification. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6638291 | ICASSP |
Keywords | Field | DocType |
semisupervised learning,indirect bridge structural health monitoring,bridge structural health monitoring,bridges (structures),learning (artificial intelligence),structural engineering,multiresolution classification framework,sensing system,semi-supervised learning,modal characteristics,moving vehicle,multiresolution classification,reliability,condition monitoring,vectors,labeling,semi supervised learning,feature extraction,learning artificial intelligence | Data mining,Sensing system,Weighting,Semi-supervised learning,Moving vehicle,Structural health monitoring,Pattern recognition,Computer science,Artificial intelligence,Condition monitoring,Machine learning,Modal | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.47 |
References | Authors | |
2 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siheng Chen | 1 | 324 | 27.85 |
| Fernando Cerda | 2 | 18 | 1.22 |
| Jia Guo | 3 | 254 | 18.16 |
| Joel B. Harley | 4 | 12 | 3.11 |
| Qing Shi | 5 | 1 | 0.47 |
| Piervincenzo Rizzo | 6 | 24 | 3.29 |
| Jacobo Bielak | 7 | 99 | 9.01 |
| James H. Garrett | 8 | 60 | 9.49 |
| Jelena Kovacevic | 9 | 802 | 95.87 |