@inproceedings{2087,
  abstract     = {{It is likely in real-world applications that only little data isavailable for training a knowledge-based system. We present a method forautomatically training the knowledge-representing membership functionsof a Fuzzy-Pattern-Classification system that works also when only littledata is available and the universal set is described insufficiently. Actually,this paper presents how the Modified-Fuzzy-Pattern-Classifier’s member-ship functions are trained using probability distribution functions.}},
  author       = {{Mönks, Uwe and Lohweg, Volker and Petker, Denis}},
  booktitle    = {{IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems}},
  keywords     = {{Fuzzy Logic, Probability Theory, Fuzzy-Pattern-Classification, Machine Learning, Artificial Intelligence, Pattern Recognition}},
  publisher    = {{28 Jun 2010 - 02 July 2010, Dortmund, Germany}},
  title        = {{{Fuzzy-Pattern-Classifier Training with Small Data Sets}}},
  year         = {{2010}},
}

@inproceedings{6356,
  author       = {{Czwalinna, R. and Wilhelm, Patrick and Lehre, Gerhard and Müller, Ulrich}},
  keywords     = {{GDL e. V., Bonn, (ISDN 3-931678-04-0)}},
  location     = {{Berlin}},
  title        = {{{Vergleich zweier Gefrierverfahren von Stutenmilch hinsichtlich der anschließenden Vakuumgefriertrocknung, Kurzfassung}}},
  year         = {{2001}},
}