Sauer, Christian, Rintala, Lotta and Roth-Berghofer, Thomas (2014) Two-phased Knowledge Formalisation for Hydrometallurgical Gold Ore process recommendation and validation. KI-Künstliche Intelligenz, 28 (4). pp. 283-295.
Two-phased Knowledge Formalisation for Hydrometallurgical Gold Ore processing.pdf - Accepted Version
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This paper describes an approach to externalising and formalising expert knowledge involved in
the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective of this
knowledge formalisation e�ffort is to create a case-based
reasoning application for recommending and validating
a treatment process of gold ores. We describe a twofold
approach to formalise the necessary knowledge. First,
formalising human expert knowledge about gold mining
situations enables the retrieval of similar mining con-
texts and respective process chains, based on prospection data gathered from a potential gold mining site.
The second aspect of our approach formalises empirical knowledge on hydrometallurgical treatments. The
latter will enable us to evaluate and, where needed,
redesign the process chain that was recommended by
the fi�rst aspect of our approach. The main problems
with the formalisation of knowledge in the gold ore
refi�nement domain are the diversity and the amount
of parameters used in literature and by experts to describe a mining context.We demonstrate how similarity
knowledge was used to formalise literature knowledge.
The evaluation of data gathered from experiments with
an initial prototype work
ow recommender, Auric Adviser, provides promising results.
|Depositing User:||Christian Sauer|
|Date Deposited:||26 May 2016 13:41|
|Last Modified:||28 Jul 2016 14:16|
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