Abstract
Abstract This paper presents the comparison of two approaches based on artificial intelligence techniques solving the task of on-line recognition of metabolic state of baker's yeast culture in a fed-batch cultivation. The first approach iS represented by a knowledge-based system containing expert knowledge in the form of production rules. The other approach is based on the application of the fuzzy neural network paradigm enabling the automatic extraction of the recognition rules from. experimental data. Performance of both approaches is discussed using results obtamed from tests on experimental data from a laboratory cultivation unit.
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