A Multilayer Interval Type-2 Fuzzy Extreme Learning Machine for the recognition of walking activities and gait events using wearable sensors

Rubio-Solis, A., Panoutsos, G. orcid.org/0000-0002-7395-8418, Beltran-Perez, C. et al. (1 more author) (2020) A Multilayer Interval Type-2 Fuzzy Extreme Learning Machine for the recognition of walking activities and gait events using wearable sensors. Neurocomputing. ISSN 0925-2312

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 Elsevier. This is an author produced version of a paper subsequently published in Neurocomputing. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Multilayer Neural Networks (ML-NNs); Fuzzy Autoencoders (FAEs); Interval Type-2 Fuzzy Logic System (IT2 FLSs); Wearable Sensors; Kernel-based ELM; Direct-defuzzification method; Extreme Learning Machine.
Dates:
  • Accepted: 30 November 2019
  • Published (online): 10 January 2020
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: 03 Dec 2019 09:42
Last Modified: 03 Feb 2020 10:12
Published Version: https://www.sciencedirect.com/science/article/pii/...
Status: Published online
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.neucom.2019.11.105

Download

Accepted Version


Embargoed until: 10 January 2021

Filename: IT2MFELM (1).pdf

Licence: CC-BY-NC-ND 4.0

Request a copy

Share / Export

Statistics