Unplanned dilution and ore-loss optimisation in underground mines via cooperative neuro-fuzzy network
| dc.contributor.author | Jang, Hyong Doo | |
| dc.contributor.supervisor | Ph.D | |
| dc.date.accessioned | 2017-01-30T09:56:32Z | |
| dc.date.available | 2017-01-30T09:56:32Z | |
| dc.date.created | 2014-12-01T23:57:38Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/997 | |
| dc.description.abstract |
The aim of study is to establish a proper unplanned dilution and ore-loss (UB: uneven break) management system. To achieve the goal, UB prediction and consultation systems were established using artificial neural network (ANN) and fuzzy expert system (FES). Attempts have been made to illuminate the UB mechanism by scrutinising the contributions of potential UB influence factors. Ultimately, the proposed UB prediction and consultation systems were unified as a cooperative neuro fuzzy system. | |
| dc.language | en | |
| dc.publisher | Curtin University | |
| dc.title | Unplanned dilution and ore-loss optimisation in underground mines via cooperative neuro-fuzzy network | |
| dc.type | Thesis | |
| dcterms.educationLevel | PhD | |
| curtin.department | Western Australian School of Mines | |
| curtin.accessStatus | Open access |