An entropy-based uncertainty measure for developing granular models

Bin Muda, M.Z. and Panoutsos, G. (2021) An entropy-based uncertainty measure for developing granular models. In: Proceedings of 2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI). 2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI), 14-15 Nov 2020, Stockholm, Sweden (Online conference). IEEE , pp. 73-77. ISBN 9781728175607

Abstract

Metadata

Authors/Creators:
  • Bin Muda, M.Z.
  • Panoutsos, G.
Copyright, Publisher and Additional Information: © 2020 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. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Granular models; Fuzzy Logic; Information Theory; Granular Computing
Dates:
  • Accepted: 10 August 2020
  • Published (online): 7 January 2021
  • Published: 7 January 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 11 Aug 2020 08:10
Last Modified: 07 Jan 2022 01:39
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/ISCMI51676.2020.9311589
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