Computational intelligence in aerospace science and engineering [Guest Editorial]

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Vasile, Massimiliano and Minisci, Edmondo and Tang, Ke (2017) Computational intelligence in aerospace science and engineering [Guest Editorial]. IEEE Computational Intelligence Magazine, 12 (4). pp. 12-13. ISSN 1556-6048 (https://doi.org/10.1109/MCI.2017.2742866)

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Abstract

The articles in this special section focus on the use of computational intelligence in the aerospace industry. In an expanding world with limited resources, Computational Intelligence has become a necessity to handle the complexity of systems and processes. The aerospace sector, in particular, has stringent performance requirements on highly complex systems for which solutions are expected to be optimal and reliable at the same time. Computational intelligence techniques have been widely used to find solutions to global single or multi-objective optimization problems, including mixed variables, multi-modal and non-differentiable quantities.

ORCID iDs

Vasile, Massimiliano ORCID logoORCID: https://orcid.org/0000-0001-8302-6465, Minisci, Edmondo ORCID logoORCID: https://orcid.org/0000-0001-9951-8528 and Tang, Ke;
  • Item type:Article
    ID code:62752
    Dates:
    Date
    Event
    1 November 2017
    Published
    11 October 2017
    Published Online
    2 August 2017
    Accepted
    Notes:(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
    Subjects:Technology > Motor vehicles. Aeronautics. Astronautics
    Department:Faculty of Engineering > Mechanical and Aerospace Engineering
    University of Strathclyde > University of Strathclyde
    Depositing user: Pure Administrator
    Date deposited:09 Jan 2018 09:50
    Last modified:17 Dec 2024 01:17
    URI:https://strathprints.strath.ac.uk/id/eprint/62752
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