Cognitive data imputation
case study in maintenance cost estimation
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.
Keywords
artificial intelligence;maintenance;cost estimation;
Data
| Language: | English |
|---|---|
| Year of publishing: | 2023 |
| Typology: | 1.01 - Original Scientific Article |
| Organization: | UL FS - Faculty of Mechanical Engineering |
| UDC: | 004.8:658.5 |
| COBISS: |
158961155
|
| ISSN: | 0007-8506 |
| Views: | 5 |
| Downloads: | 0 |
| Average score: | 0 (0 votes) |
| Metadata: |
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Other data
| Secondary language: | Slovenian |
|---|---|
| Secondary keywords: | umetna inteligenca;vzdrževanje;ocena stroškov; |
| Type (COBISS): | Article |
| Pages: | str. 385-388 |
| Volume: | ǂVol. ǂ72 |
| Issue: | ǂiss. ǂ1 |
| Chronology: | 2023 |
| DOI: | 10.1016/j.cirp.2023.03.036 |
| ID: | 19574776 |
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