Hybrid knowledge-based tool for mixing equipment selection - The fuzzy neural network

被引:1
|
作者
Kraslawski, A [1 ]
Pedrycz, W [1 ]
Koiranen, T [1 ]
Nystrom, L [1 ]
机构
[1] UNIV MANITOBA,DEPT ELECT & COMP ENGN,WINNIPEG,MB R3T 2N2,CANADA
关键词
D O I
10.1002/ceat.270190307
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The hybrid knowledge-based system proposed in this paper consists of a ''stiff'' segment, viz. the expert system based on the object-oriented approach, and a flexible part, viz. the neural network. Some of the input parameters of the problem and output parameters of the ''stiff'' system are presented as the fuzzy numbers. Detailed information is also presented about the development of the neural network. The most evident advantages of the proposed introduction of a hybrid architecture of the knowledge-based system are a faster evaluation and generation of design alternatives and support of systematic searches and storage of experience. In addition, the resulting ability to extrapolate results would be unattainable with separately acting stiff and flexible systems. A system for the estimation of the parameters of a mixing system for wastewater treatment is presented as an example to illustrate the principles of the hybrid system.
引用
收藏
页码:233 / 239
页数:7
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