A New Algorithm of Similarity Measuring for Multi-experts’ Qualitative Knowledge Based on Outranking Relations in Case-Based Reasoning Methodology
Qualitative knowledge reasoning is a key content in knowledge science. Case-based reasoning is one of the main reasoning methodologies in artificial intelligence. Outranking relation methods, called ELECTRE and others, have been developed. In this research, a new algorithm of similarity measuring for qualitative problems in the presence of multiple experts based on outranking relations in case-based reasoning was proposed. Strict preference, weak preference, and indifference relations were introduced to formulate imprecision, uncertainty, incompleteness knowledge from multi-experts. Case similarities were integrated through aggregating house on the foundation of outranking relations. Experiments indicated that the new algorithm got accordant outcome with traditional quantitative similarity mode but extended its application range.
KeywordsActual Preference Similarity Algorithm Concordance Index Multiple Expert Indifference Relation
Unable to display preview. Download preview PDF.
- Turban, E., Aronson, J.E.: Decision Support Systems and Intelligent Systems, 6th edn. Prentice International Hall, Hong Kong (2001)Google Scholar
- Schank, R.C.: Dynamic Memory: A Theory of Learning in Computers and People. Cambridge University Press, New York (1982)Google Scholar
- Aamodt, A., Plaza, E.: Case-based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Artificial Intelligence Communications 7, 39–59 (1994)Google Scholar
- Hunt, J.: Evolutionary Case Based Design. In: Watson, I.D. (ed.) UK CBR 1995. LNCS, vol. 1020, pp. 17–31. Springer, Heidelberg (1995)Google Scholar
- Chen, Z.-X.: Improved Algorithms of ELECTRE-I for Production Order Evaluation. Group Technology & Production Modernization 22, 19–21 (2005)Google Scholar