Abstract
In the paper we propose a new method for designing and reduction of neuro-fuzzy systems for stroke diagnosis. The concept of the weighted parameterized triangular norms is applied and neuro-fuzzy systems based on fuzzy S-implications are derived. In subsequent stages we reduce the linguistic model. The results are implemented to solve the problem of stroke diagnosis.
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Cpałka, K., Rebrova, O., Rutkowski, L. (2009). A New Method for Complexity Reduction of Neuro-fuzzy Systems with Application to Differential Stroke Diagnosis. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04277-5_44
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DOI: https://doi.org/10.1007/978-3-642-04277-5_44
Publisher Name: Springer, Berlin, Heidelberg
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