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Sustaining implicit learning in locomotive operation
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0001-8693-3431
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-3827-0295
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0001-8111-6918
2018 (English)In: 20th Nordic Seminar on Railway Technology: Abstracts, Gothenburg, Sweden: Chalmers University of Technology , 2018, p. 59(65)-59(65)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Modern trains are capable of monitoring health status in real time and infer behaviour of various systems. This trend will grow with advancements of machine learning those will produce feedback for continuously improving the prediction models. Despite reduced physical connectivity of human with locomotive systems, human interference will be required for critical decision-making. Human implicit learning involves the largely unconscious learning of dynamic statistical patterns and features, which leads to the development of tacit knowledge1. Pirsig2 argued that “each machine has its own, unique personality which probably could be defined as the intuitive sum total of everything you know and feel about it”. Theses suggest that humans employ an intuitive cognition ability that leads to developing implicit knowledge and interactions with machines. In this study, we focus on signifying the implicit knowledge in locomotive operation context and seek ways to facilitate effective decision-making

Place, publisher, year, edition, pages
Gothenburg, Sweden: Chalmers University of Technology , 2018. p. 59(65)-59(65)
Keywords [en]
implicit learning, locomotive operation, intuition
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-76529OAI: oai:DiVA.org:ltu-76529DiVA, id: diva2:1366029
Conference
20th Nordic Seminar on Railway Technology, 12-13 June, 2018, Gothenburg, Sweden
Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2020-09-23Bibliographically approved

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http://www.charmec.chalmers.se/NJS18/NJS18_Abstracts_180607.pdf

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Illankoon, PrasannaTretten, PhillipKumar, Uday

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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