Abstract
Conventional experimental/knowledge records (usually tables, graphs and/or equations) are not suitable for an efficient uncertainty-reasoning because of the poor knowledge-acquisition methods used to develop them. A fuzzy knowledge base is a suitable framework for acquisition of vague, sparse and inconsistent knowledge. A revitalization of valuable records and re-used literature knowledge items is a retrospective application of knowledge engineering algorithms. This is an ad hoc process and a general theoretical background does not exist. Therefore this paper presents a detailed description of a case study (49 variables, 4000 statements).A query as an element of a man-machine dialogue is presented. No a priori knowledge of fuzzy mathematics is needed.
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