Cognitive data imputation: case study in maintenance cost estimation
| dc.contributor.author | Erkoyuncu, John Ahmet | |
| dc.contributor.author | Namoano, Bernadin | |
| dc.contributor.author | Kozjek, Dominik | |
| dc.contributor.author | Vrabič, Rok | |
| dc.date.accessioned | 2023-08-08T10:53:25Z | |
| dc.date.available | 2023-08-08T10:53:25Z | |
| dc.date.issued | 2023-07-13 | |
| dc.description.abstract | 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. | en_UK |
| dc.identifier.citation | Erkoyuncu JA, Namoano B, Kozjek D, Vrabic R. (2023) Cognitive data imputation: case study in maintenance cost estimation. CIRP Annals - Manufacturing Technology, Volume 72, Issue 1, July 2023, pp. 385-388 | en_UK |
| dc.identifier.issn | 0007-8506 | |
| dc.identifier.uri | https://doi.org/10.1016/j.cirp.2023.03.036 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/20060 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Elsevier | en_UK |
| dc.rights | Attribution 4.0 International | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | artificial intelligence | en_UK |
| dc.subject | maintenance | en_UK |
| dc.subject | cost estimation | en_UK |
| dc.title | Cognitive data imputation: case study in maintenance cost estimation | en_UK |
| dc.type | Article | en_UK |