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.

Abstract

Metadata

Related URLs:
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

Download

Final eThesis - complete (pdf)

Filename: Armani_PhD_thesis_resubmission_grerrors_corrected.pdf

Licence: Creative Commons Attribution Non-commercial Share Alike (UK)

Share / Export


You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.