Abstract
A fractal/chaos analysis and discriminative power evaluation of knowledge bases are presented. They can be used by knowledge engineers to make knowledge acquisition activities more objective. The fractal analysis gives a numerical parameter (fractal dimension). It describes certain relations between general and specific knowledge items (for example between on-line measurements and general rules of thumbs). The discriminative power analysis is used to quantify one aspect of a knowledge base “quality.” Both formal tools are applicable regardless of types of knowledge bases. The article describes their fuzzy interpretations. A simple demonstrative example (a set of 17 fuzzy statements) and a realistic fractal recommendation (fuzzy versus neural control algorithms) are presented in detail.
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