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Parallel genetic algorithms for the solution of inverse heat conduction problems

Parallel genetic algorithms for the solution of inverse heat conduction problems

Guo, Q., Shen, D., Guo, Y. and Lai, Choi-Hong (2007) Parallel genetic algorithms for the solution of inverse heat conduction problems. International Journal of Computer Mathematics, 84 (2). pp. 241-250. ISSN 0020-7160 (doi:10.1080/00207160601169967)

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Abstract

A parallel genetic algorithm (PGA) is proposed for the solution of two-dimensional inverse heat conduction problems involving unknown thermophysical material properties. Experimental results show that the proposed PGA is a feasible and effective optimization tool for inverse heat conduction problems

Item Type: Article
Uncontrolled Keywords: heat conduction, inverse problem, parallel genetic algorithm
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Science & Engineering Group
Related URLs:
Last Modified: 14 Oct 2016 09:03
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/1144

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