Development of industrial process characterisation through data analysis

Josifovic, Aleksandar and Corney, Jonathan; (2017) Development of industrial process characterisation through data analysis. In: 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. IEEE, GRC. ISBN 978-1-5090-4241-8

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    Abstract

    Recently the world has seen an explosion of available data, gathered from sensors, experiments and direct measurements. The engineering world is shifting from model-centred simulations to the exploitation of large datasets for insights into machine behaviour. In the case of optimisation, where usually a simulation model is provided for the exploration of the parameter space, the new data-driven approach translates into the use of data for quantifying problems and delivering an optimal solution.

    Creators(s): Josifovic, Aleksandar ORCID logoORCID: https://orcid.org/0000-0003-4024-6729 and Corney, Jonathan ORCID logoORCID: https://orcid.org/0000-0003-1210-3827;
    Item type:Book Section
    ID code:61597
    Notes:(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Keywords:oil technology, accelerometers, data aquisition, Electrical engineering. Electronics Nuclear engineering, Computer Networks and Communications, Information Systems and Management, Control and Optimization, Artificial Intelligence
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Design, Manufacture and Engineering Management
    Strategic Research Themes > Innovation Entrepreneurship
    Depositing user: Pure Administrator
    Date deposited:17 Aug 2017 13:16
    Last modified:26 Nov 2020 03:15
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/61597
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