Foundations of neural networks
Foundations of neural networks
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Generating optimal adaptive fuzzy-neural models of dynamicalsystems with applications to control
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Approximation accuracy analysis of fuzzy systems as function approximators
IEEE Transactions on Fuzzy Systems
Fuzzy basis functions: comparisons with other basis functions
IEEE Transactions on Fuzzy Systems
Time-Invariant Dynamic Systems identification based on the qualitative features of the response
Engineering Applications of Artificial Intelligence
Learning from biomedical time series through the integration of qualitative models and fuzzy systems
Artificial Intelligence in Medicine
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This paper presents a novel approach to non-linear black-box system identification which combines Qualitative Reasoning (QR) methods with fuzzy logic systems. Such a method aims at building a good initialization of a fuzzy identifier, so that it will converge to the input-output relation which captures the nonlinear dynamics of the system. Fuzzy inference procedures should be initialized with a rule-base predefined by the human expert: when such a base is not available or poorly defined, the inference procedure becomes extremely inefficient. Our method aims at solving the problem of the construction of a meaningful rule-base: fuzzy rules are automatically generated by encoding the knowledge of the system dynamics described by the outcomes of its qualitative simulation. Both efficiency and robustness of the method are demonstrated by its application to the identification of the kinetics of Thiamine (vitamin B1) and its phosphoesters in the cells of the intestine tissue.