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http://bura.brunel.ac.uk/handle/2438/4835
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DC Field | Value | Language |
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dc.contributor.author | Abbod, MF | - |
dc.contributor.author | Mahfouf, M | - |
dc.contributor.author | Linkens, DA | - |
dc.date.accessioned | 2011-03-18T14:37:21Z | - |
dc.date.available | 2011-03-18T14:37:21Z | - |
dc.date.issued | 1998 | - |
dc.identifier.citation | IEE Conference Publication, 2(455): 1575-1580, Sep 1998 | en_US |
dc.identifier.isbn | 0-85296-708-X | - |
dc.identifier.issn | 0537-9989 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=726154 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/4835 | - |
dc.description | This is the post-print version of the article. The official published version can be accessed from the link below. | en_US |
dc.description.abstract | A multi-objective genetic algorithm is developed for the purpose of optimizing the rule-base of a Self-Organising Fuzzy Logic Control algorithm (SOFLC). The tuning of the SOFLC optimization is based on selection of the best shaped performance index for modifying the rule-base on-line. A comparative study is conducted between various methods of multi-objective genetic optimisation using the SOFLC algorithm on the muscle relaxant anaesthesia system, which includes a severe non-linearity, varying dynamics and time-delay. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Fuzzy logic | en_US |
dc.subject | Self-organising | en_US |
dc.subject | Multi-objective optimisation | en_US |
dc.title | Multi-objective genetic optimisation for self-organising fuzzy logic control | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1049/cp:19980464 | - |
Appears in Collections: | Electronic and Electrical Engineering Dept of Electronic and Electrical Engineering Research Papers |
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Fulltext.pdf | 132.53 kB | Adobe PDF | View/Open |
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