Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72653
Title: Fuzzy modeling of nonlinear pH processes through neural approach
Authors: Nie, Junhong 
Loh, A.P. 
Hang, C.C. 
Issue Date: 1994
Source: Nie, Junhong,Loh, A.P.,Hang, C.C. (1994). Fuzzy modeling of nonlinear pH processes through neural approach. IEEE International Conference on Fuzzy Systems 2 : 1224-1229. ScholarBank@NUS Repository.
Abstract: 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.
Source Title: IEEE International Conference on Fuzzy Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/72653
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