|Fuzzy Data Analysis||Uncertainty and Vagueness in Knowledge Based Systems|
Neural Networks and Fuzzy Systems
In our group we work on theoretical foundations of neuro-fuzzy systems, and practical realizations of these concepts. Neural networks can learn from data, but cannot be interpreted - they are black boxes to the user. Fuzzy Systems consist of interpretable linguistic rules, but they cannot learn. We use learning algorithms from the domain of neural networks to create fuzzy systems from data. The learning algorithms can learn both fuzzy sets, and fuzzy rules, and can also use prior knowledge.
What are neuro-fuzzy systems? Read about our view of these combinations of fuzzy systems with neural network methods.
Based on our research activities we have developed several neuro-fuzzy models:
If you want to know more about our work please have a look at our list of publications, or choose a paper from our list of papers (with abstracts) and download it.
For further information please contact Detlef Nauck, Andreas Nürnberger, or Rudolf Kruse.