This project explores how fuzzy technologies and neural networks enhance process control in the rubber industry.
Fuzzy technologies as well as neural networks are being used in process industry to an increasing degree. Due to the complexity and non-linearity of most of the processes under consideration exact mathematical models are often difficult or even impossible to establish. The two aforementioned intelligent technologies aim at different strategies to solve the respective problems. Fuzzy systems enable experts to formulate their knowledge and to integrate it into a computer as basis for automated decisions and control strategies. Neural networks have the capability to learn relations in process data (1) . This paper describes a project where neural networks have been used for process analysis in rubber industry.
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Angstenberger et al. (1999) studied this question.
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