| dc.contributor.author |
Barai, Sudhir Kumar |
|
| dc.date.accessioned |
2021-11-14T07:45:09Z |
|
| dc.date.available |
2021-11-14T07:45:09Z |
|
| dc.date.issued |
2006 |
|
| dc.identifier.uri |
https://link.springer.com/chapter/10.1007/3-540-31662-0_3 |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/3587 |
|
| dc.description.abstract |
It is of utmost important to maintain perfect condition of complex welded structures such as pressure vessels, load bearing structural members and power plants. The commonly used approach is non-destructive evaluation (NDE) of such welded structures. This paper presents an application of artificial neural networks (ANN) for weld data, extracted from reported radiographic images. Linear Vector Quantization based supervised neural network classifier is implemented in Parallel Processing Environment on PARAM 10000. Single Architecture Single Processor and Single Architecture Multiple Processor based parallel neuro classifier are developed for the weld defect classification. The results obtained for various statistical evaluation methods showed promising future of Single Architecture Single Processor based parallel neuro classifier in the problem domain. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Springer |
en_US |
| dc.subject |
Civil Engineering |
en_US |
| dc.subject |
Neural Network Model |
en_US |
| dc.subject |
Message Passing Interface |
en_US |
| dc.subject |
Learn Vector Quantization |
en_US |
| dc.title |
Parallel Neuro Classifier for Weld Defect Classification |
en_US |
| dc.type |
Article |
en_US |