Development of a hybrid genetic programming technique for computationally expensive optimisation problems

Armani, Umberto (2014) Development of a hybrid genetic programming technique for computationally expensive optimisation problems. PhD thesis, University of Leeds.

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Keywords: genetic programming, evolutionary algorithms, optimisation, symbolic regression, metamodels, inference, machine learning, explicit models
Awarding institution: University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Civil Engineering (Leeds)
Identification Number/EthosID (e.g. uk.bl.ethos.123456): uk.bl.ethos.631392
Depositing User: Dr Umberto Armani
Date Deposited: 27 Nov 2014 11:13
Last Modified: 25 Nov 2015 13:47

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