ISSN:
1573-773X
Keywords:
classification of seismic events
;
fuzzy logic
;
half-distributed coding
;
incomplete data
;
learning
;
multi-layer perceptron
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract This letter presents a method for modelling and processing incomplete data in connectionist systems. The approach consists in applying a neuro-fuzzy coding to the input data of a neural network. After an introduction to the different kinds of imperfections, we propose a neuro-fuzzy coding in order to take incomplete data into account. We show the efficiency of this coding on the problem of the classification of seismic events. The results show that a neuro-fuzzy coding of the inputs of a neural network increases the performance and classifies incomplete data with little affect on the results.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1009621214099
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