Two-phased knowledge formalisation for hydrometallurgical gold ore process recommendation and validation

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. ISSN 0933-1875

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Abstract

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 was to create a case-based reasoning application for recommending and validating a treatment process of gold ores. We describe a twofold approach. Formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. Secondly, empirical knowledge on hydrometallurgical treatments is formalised. This enabled us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with formalisation of knowledge in the domain of gold ore refinement 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 workflow recommender, Auric Adviser, provides promising results.

Item Type: Article
Additional Information: © Springer-Verlag Berlin Heidelberg 2014. The final publication is available at Springer via https://doi.org/10.1007/s13218-014-0315-2.
Uncontrolled Keywords: Knowledge formalisation, Hydrometallurgy, Case-based reasoning
Subjects: Computing
Depositing User: Christian Sauer
Date Deposited: 26 May 2016 13:41
Last Modified: 28 Mar 2017 09:23
URI: http://repository.uwl.ac.uk/id/eprint/2185

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