Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/62427
DC Field | Value | |
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dc.title | Modeling pH neutralization processes using fuzzy-neural approaches | |
dc.contributor.author | Nie, J. | |
dc.contributor.author | Loh, A.P. | |
dc.contributor.author | Hang, C.C. | |
dc.date.accessioned | 2014-06-17T06:50:55Z | |
dc.date.available | 2014-06-17T06:50:55Z | |
dc.date.issued | 1996 | |
dc.identifier.citation | Nie, J.,Loh, A.P.,Hang, C.C. (1996). Modeling pH neutralization processes using fuzzy-neural approaches. Fuzzy Sets and Systems 78 (1) : 5-22. ScholarBank@NUS Repository. | |
dc.identifier.issn | 01650114 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/62427 | |
dc.description.abstract | This paper is concerned with the modeling and identification of pH-processes via fuzzy-neural approaches. A simplified fuzzy model acting as an approximate reasoner is used to deduce the model output on the basis of the identified rule-base which is derived by using one of the following three network-based self-organizing algorithms: unsupervised self-organizing counter-propagation network (USOCPN), supervised self-organizing counter-propagation network (SSOCPN), and self-growing adaptive vector quantization (SGAVQ). Three typical pH processes were treated including a strong acid-strong base system, a weak acid-strong base system, and a two-output system with buffering taking part in reaction. Extensive simulations including on-line modeling have shown that these nonlinear pH-processes can be modeled reasonably well by the present schemes which are simple but efficient. © 1996 - Elsevier Science B.V. All rights reserved. | |
dc.source | Scopus | |
dc.subject | Fuzzy modeling | |
dc.subject | Fuzzy-neural systems | |
dc.subject | Neural networks | |
dc.subject | pH nonlinear process | |
dc.subject | Process control | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | Fuzzy Sets and Systems | |
dc.description.volume | 78 | |
dc.description.issue | 1 | |
dc.description.page | 5-22 | |
dc.description.coden | FSSYD | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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