Title :
FDIMLP: A new neuro-fuzzy model
Author_Institution :
Comput. Sci. Centre, Geneva Univ., Switzerland
Abstract :
We present a neuro-fuzzy model called fuzzy discretized interpretable multi-layer perceptron (FDIMLP). Fuzzy rules are extracted in polynomial time with respect to the size of the problem and the size of the network. We applied our model to three classification problems of the public domain. It turned out that FDIMLP networks compared favorably with respect to EFuNN and ANFIS neuro-fuzzy systems
Keywords :
fuzzy logic; fuzzy neural nets; fuzzy set theory; learning (artificial intelligence); multilayer perceptrons; ANFIS; EFuN; FDIMLP; classification problems; fuzzy discretized interpretable multi-layer perceptron; fuzzy rules; neuro-fuzzy model; polynomial time; Artificial intelligence; Computer science; Fuzzy logic; Fuzzy neural networks; Humans; Intelligent systems; Multilayer perceptrons; Neurons; Polynomials; Uncertainty;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939554
