Monitoring of metallurgical plant performance with Bayesian change point detection algorithms
Production data on mineral processing plants often show great variability, owing to measurement errors, changes in plant performance related to changes in ore characteristics or operating conditions, etc. This makes it difficult to assess plant performance where new equipment or reagents are being e...
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| Format: | Conference Paper |
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Gecamin
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/36033 |