Predicting the hardgrove grindability index using interpretable decisiontreebased machine learning models
| dc.article.end-page | 16 | en |
| dc.article.start-page | 1 | en |
| dc.citation.doi | 10.1016/J.FUEL.2024.133953 | en |
| dc.contributor.author | Y Chen | en |
| dc.contributor.author | M Khandelwal | en |
| dc.contributor.author | m Onifade | en |
| dc.contributor.author | J Zhou | en |
| dc.contributor.author | A I Lawal | en |
| dc.contributor.author | Oluwaseyi Bada | en |
| dc.contributor.author | Bekir Genc | en |
| dc.date.accessioned | 2025-07-16T09:44:48Z | |
| dc.faculty | FACULTY OF ENGINEERING & THE BUILT ENVIRONMENT | en |
| dc.identifier.citation | WOS | en |
| dc.identifier.issn | 0016-2361 | en |
| dc.identifier.uri | https://hdl.handle.net/10539/45517 | |
| dc.journal.title | Predicting the hardgrove grindability index using interpretable decisiontreebased machine learning models | en |
| dc.journal.volume | 384 | en |
| dc.publisher | ELSEVIER SCI LTD | en |
| dc.school | 3.07 | en |
| dc.title | Predicting the hardgrove grindability index using interpretable decisiontreebased machine learning models | en |
| dc.type | Journal Article | en |
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