Deep Learning Decision Support for Sustainable Asset Management

Marianne Cherrington, Zhongyu (joan) Lu, Qiang Xu, David Airehrour, Samaneh Madanian, Andrea Dyrkacz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sustainable decisions can be thwarted by a plethora of conflicting influences and information, yet the need to prioritise sustainability in management has never been greater. In an era of high- and ultra-high dimensional data, deep learning models offer the scalability required to extract good representations of significant features from raw data. With automatic learning at several levels of abstraction, deep learning can support sustainable asset management by learning complex functions mapping of systems. By processing data directly from input to output, clear and concise information can support visionary asset management whilst exposing hidden insights, detecting anomalies or predicting future states. This research will look at the necessity of applying deep learning in sustainable asset management and reveal some of the challenges that exist.
Original languageEnglish
Title of host publicationAdvances in Asset Management and Condition Monitoring
Subtitle of host publicationCOMADEM 2019
EditorsAndrew Ball, Len Gelman, B. K. N. Rao
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Chapter45
Pages537-547
Number of pages11
Volume166
Edition1st
ISBN (Electronic)9783030577452
ISBN (Print)9783030577445
DOIs
Publication statusPublished - 28 Aug 2020
Event32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference - University of Huddersfield, Huddersfield, United Kingdom
Duration: 3 Sep 20195 Sep 2019
Conference number: 32
http://www.comadem2019.com/ (Link to Conference Website)

Publication series

NameSmart Innovation, Systems and Technologies
Volume166
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference
Abbreviated titleCOMADEM 2019
CountryUnited Kingdom
CityHuddersfield
Period3/09/195/09/19
Internet address

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  • Cite this

    Cherrington, M., Lu, Z. ., Xu, Q., Airehrour, D., Madanian, S., & Dyrkacz, A. (2020). Deep Learning Decision Support for Sustainable Asset Management. In A. Ball, L. Gelman, & B. K. N. Rao (Eds.), Advances in Asset Management and Condition Monitoring: COMADEM 2019 (1st ed., Vol. 166, pp. 537-547). (Smart Innovation, Systems and Technologies; Vol. 166). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-57745-2_45