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Process Identification through modular neural networks and rule extraction

vanderZwaag, B J ; Slump, C H and Spaanenburg, Lambert LU (2002) 5th International Conference on Computational Intelligent Systems for Applied Research (FLINS) p.268-277
Abstract
Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule extraction is performed module by module. This has all the benefits of a divide-and-conquer method and opens the way to structured design. This paper discusses a next step in this direction by illustrating the potential of base functions to design the neural model
Please use this url to cite or link to this publication:
author
; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Neural Networks, Modularity, Functional Base, Process Model, Rule Extraction
host publication
Proceedings FLINS 2002
pages
268 - 277
conference name
5th International Conference on Computational Intelligent Systems for Applied Research (FLINS)
conference location
Gent, Belgium
conference dates
2002-09-16 - 2002-09-18
language
English
LU publication?
no
id
a7fb62ac-a8cf-4f96-a6c8-ccfc0c1da9fc (old id 603905)
date added to LUP
2016-04-04 13:22:38
date last changed
2018-11-21 21:13:33
@inproceedings{a7fb62ac-a8cf-4f96-a6c8-ccfc0c1da9fc,
  abstract     = {{Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule extraction is performed module by module. This has all the benefits of a divide-and-conquer method and opens the way to structured design. This paper discusses a next step in this direction by illustrating the potential of base functions to design the neural model}},
  author       = {{vanderZwaag, B J and Slump, C H and Spaanenburg, Lambert}},
  booktitle    = {{Proceedings FLINS 2002}},
  keywords     = {{Neural Networks; Modularity; Functional Base; Process Model; Rule Extraction}},
  language     = {{eng}},
  pages        = {{268--277}},
  title        = {{Process Identification through modular neural networks and rule extraction}},
  year         = {{2002}},
}