Network Performance Assessment for Neurofuzzy Data Modelling
Network Performance Assessment for Neurofuzzy Data Modelling
This paper evaluates the performance of ten significance measures applied to the problem of determining an appropriate network structure, for data modelling with neurofuzzy systems. The advantages of Neurofuzzy systems are demonstrated with application to both real and synthetic data interpretation problems.
313--323
Gunn, S.R.
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Brown, M.
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Bossley, K.M.
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Liu, X.
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Cohen, P.
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Berthold, M.
bb5fb18f-8b30-4faa-bd76-391a53310bbb
1997
Gunn, S.R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Bossley, K.M.
de1a2979-b9e9-481e-af09-0b4887f0f360
Liu, X.
878efcac-76c6-4ca0-8f4a-425f1e9abdac
Cohen, P.
5d32b753-711a-4633-8c27-eb9871f50699
Berthold, M.
bb5fb18f-8b30-4faa-bd76-391a53310bbb
Gunn, S.R., Brown, M. and Bossley, K.M.
(1997)
Network Performance Assessment for Neurofuzzy Data Modelling.
Liu, X., Cohen, P. and Berthold, M.
(eds.)
Lecture Notes in Computer Science.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
This paper evaluates the performance of ten significance measures applied to the problem of determining an appropriate network structure, for data modelling with neurofuzzy systems. The advantages of Neurofuzzy systems are demonstrated with application to both real and synthetic data interpretation problems.
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More information
Published date: 1997
Venue - Dates:
Lecture Notes in Computer Science, 1997-01-01
Organisations:
Electronic & Software Systems
Identifiers
Local EPrints ID: 250037
URI: http://eprints.soton.ac.uk/id/eprint/250037
PURE UUID: 5386fd04-d80b-4ac4-8b58-bbd8d9e464d1
Catalogue record
Date deposited: 29 Oct 2001
Last modified: 08 Jan 2022 08:45
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Contributors
Author:
S.R. Gunn
Author:
M. Brown
Author:
K.M. Bossley
Editor:
X. Liu
Editor:
P. Cohen
Editor:
M. Berthold
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