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Supporting data for 'Cognitive data imputation: Case study in maintenance cost estimation'

Version 2 2023-06-08, 14:14
Version 1 2023-03-31, 14:12
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posted on 2023-06-08, 14:14 authored by John ahmet ErkoyuncuJohn ahmet Erkoyuncu, Bernadin NamoanoBernadin Namoano

  

Cost estimation is critical for effective decision making in engineering projects. However, it is often hampered by a lack of sufficient data. For this, data imputation techniques can be used to estimate missing costs based on statistical estimates or analogies with historical data. However, these techniques are often limited because they do not consider the existing knowledge of experts. In this paper, a novel cognitive data imputation technique is proposed for cost estimation that uses explanatory interactive machine learning to integrate and improve human knowledge. Through a case study in maintenance cost estimation the effectiveness of the approach is demonstrated. 

Funding

Digital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)

Engineering and Physical Sciences Research Council

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Authoriser (e.g. PI/supervisor)

j.a.erkoyuncu@cranfield.ac.uk

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