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Fuzzy modeling of nonlinear pH processes through neural approach

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3 Author(s)
Nie, Junhong ; Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore ; Loh, A.P. ; Hang, C.C.

This paper is concerned with the modeling and identification of nonlinear 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 network-based self-organizing algorithms. Two typical pH processes were treated including a weak acid-strong base system and a two-output system with buffering taking part in reaction. Simulation results have shown that these nonlinear pH-processes can be modeled reasonably well by the present schemes which are simple but efficient

Published in:

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Date of Conference:

26-29 Jun 1994

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