Weld residual stress prediction using artificial neural network and Fuzzy logic modeling
IR@NISCAIR: CSIR-NISCAIR, New Delhi - ONLINE PERIODICALS REPOSITORY (NOPR)
View Archive Info| Field | Value | |
| Creator |
Dhas, J Edwin Raja
Kumanan, Somasundaram |
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| Date |
2011-12-09T11:56:19Z
2011-12-09T11:56:19Z 2011-10 |
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| Identifier |
0975-1017 (Online); 0971-4588 (Print)
http://hdl.handle.net/123456789/13241 |
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| Description |
351-360
intelligent tools such as expert systems, artificial neural network and fuzzy logic support decision-making are being used in intelligent manufacturing systems. Success of intelligent manufacturing systems depends on effective and efficient utilization of intelligent tools. <span style="mso-bidi-font-weight:bold">Weld residual stress depends on different process parameters and its prediction and control is a challenge to the researchers. In this paper, intelligent predictive techniques artificial neural network (ANN) and fuzzy logic models are developed for weld residual stress prediction. The models are developed<span style="mso-bidi-font-weight:bold"> using Matlab toolbox functions<span style="mso-bidi-font-weight:bold">. Data set required to train the models are obtained through finite element simulation. Results from the fuzzy model are compared with the developed <span style="mso-bidi-font-weight: bold">artificial neural network model, and these models are also validated. </span></span></span></span> |
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| Language |
en_US
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| Publisher |
NISCAIR-CSIR, India
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| Rights |
<img src='http://nopr.niscair.res.in/image/cc-license-sml.png'> <a href='http://creativecommons.org/licenses/by-nc-nd/2.5/in' target='_blank'>CC Attribution-Noncommercial-No Derivative Works 2.5 India</a>
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| Source |
IJEMS Vol.18(5) [October 2011]
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| Subject |
Weld residual stress
Artificial neural network Fuzzy logic Finite element analysis |
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| Title |
Weld residual stress prediction using artificial neural network and Fuzzy logic modeling
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| Type |
Article
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