|
Digital Library of the
European Council for Modelling and Simulation |
Title: |
Classification Of Machine Operations Based On Growing Neural Models
And Fuzzy Decision |
Authors: |
Gancho Vachkov |
Published in: |
ECMS
2007 Proceedings Edited
by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni ISBN:
978-0-9553018-2-7 Doi: 10.7148/2007 21st European
Conference on Modelling and Simulation, Prague, June
4-6, 2007 |
Citation
format: |
Vachkov, G. (2007). Classification Of
Machine Operations Based On Growing Neural Models And Fuzzy Decision. ECMS
2007 Proceedings edited by: I. Zelinka, Z. Oplatkova, A. Orsoni
(pp. 68-73). European Council for Modeling and Simulation. doi:10.7148/2007-0068. |
DOI: |
http://dx.doi.org/10.7148/2007-0068 |
Abstract: |
In
this paper, a novel approach to analysis and classification of complex
machine operations is presented. The available data sets from different
machine operations are first compressed and saved in the form of neural
models that are called compressed information models (CIM). Here an original
algorithm for unsupervised learning is proposed. It creates the so called growing neural models in a sense that the number
of neurons is gradually increasing (growing) during the learning process,
until predetermined model accuracy (the “average minimum distance”) is
satisfied. The proposed algorithm has much faster convergence compared with
the classical neural-gas learning that uses preliminary fixed number of
neurons. A
special Knowledge Base classification scheme is also proposed in the paper.
It uses a fuzzy decision block for computing the difference degree between
each CIM in the Knowledge Base with the CIM of the current machine operation.
The fuzzy inference procedure uses two parameters for comparison the CIMs, namely the decision the Center-of-Gravity and the
General Size of the CIM. An example for classification of
45 specially generated operations from a diesel engine of a hydraulic
excavator is used to demonstrate the whole proposed technology and its applicability.
This fuzzy classification
scheme is also able to discover new operations that significantly differ from
all previously known operations. |
Full
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