Abstract
In this paper we discuss information fusion in neuro-fuzzy systems in the context of intelligent data analysis. As information sources we consider human experts who formulate their knowledge in form of fuzzy if-then rules, and databases of sample data. We discuss how to fuse these different types of knowledge by using neuro-fuzzy methods and present some experimental results. We show how neuro-fuzzy approaches can fuse fuzzy rule sets, induce a rule base from data and revise a rule set in the light of training data.
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Nauck, D.D., Kruse, R. (2001). Information Fusion in Neuro-Fuzzy Systems. In: Della Riccia, G., Lenz, HJ., Kruse, R. (eds) Data Fusion and Perception. International Centre for Mechanical Sciences, vol 431. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2580-9_4
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DOI: https://doi.org/10.1007/978-3-7091-2580-9_4
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