Parameter identification and damage detection using evolutionary programming
This study develops a general approach based on evolutionary programming (EP) as a backcalculation algorithm for structural nondestructive evaluation (NDE). Although EP has been proven to be robust in finding the global optimum, the speed of convergence could be slow for certain problems. This thesi...
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sg-ntu-dr.10356-121322023-03-03T19:29:55Z Parameter identification and damage detection using evolutionary programming Xu, Jianfeng Soh Chee Kiong School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering::Structures and design This study develops a general approach based on evolutionary programming (EP) as a backcalculation algorithm for structural nondestructive evaluation (NDE). Although EP has been proven to be robust in finding the global optimum, the speed of convergence could be slow for certain problems. This thesis presents an EP algorithm hybridized with local search strategies. Numerical experiments show that the algorithm improves the search efficiency of the traditional EP method without loss of effectiveness in finding the global optimum. The high search efficiency and effectiveness enhance the feasibility and practicality of applying an EP-based backcalculation algorithm for structural NDE. Doctor of Philosophy (CEE) 2008-09-25T06:38:06Z 2008-09-25T06:38:06Z 2005 2005 Thesis Xu, J. F. (2005). Parameter indentification and damage detection using evolutionary programming. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/12132 10.32657/10356/12132 en Nanyang Technological University 215 p. application/pdf |
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DRNTU::Engineering::Civil engineering::Structures and design Xu, Jianfeng Parameter identification and damage detection using evolutionary programming |
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This study develops a general approach based on evolutionary programming (EP) as a backcalculation algorithm for structural nondestructive evaluation (NDE). Although EP has been proven to be robust in finding the global optimum, the speed of convergence could be slow for certain problems. This thesis presents an EP algorithm hybridized with local search strategies. Numerical experiments show that the algorithm improves the search efficiency of the traditional EP method without loss of effectiveness in finding the global optimum. The high search efficiency and effectiveness enhance the feasibility and practicality of applying an EP-based backcalculation algorithm for structural NDE. |
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Soh Chee Kiong |
author_facet |
Soh Chee Kiong Xu, Jianfeng |
format |
Theses and Dissertations |
author |
Xu, Jianfeng |
author_sort |
Xu, Jianfeng |
title |
Parameter identification and damage detection using evolutionary programming |
title_short |
Parameter identification and damage detection using evolutionary programming |
title_full |
Parameter identification and damage detection using evolutionary programming |
title_fullStr |
Parameter identification and damage detection using evolutionary programming |
title_full_unstemmed |
Parameter identification and damage detection using evolutionary programming |
title_sort |
parameter identification and damage detection using evolutionary programming |
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2008 |
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https://hdl.handle.net/10356/12132 |
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1759857000276033536 |