December 2001


Novel neural fuzzy network for product quality monitoring

Unique combination of the two technologies provided good results on reformer octane

Jia, L., Yu, J., Research Institute of Automation, East China University of Science and Technology

A novel self-organizing neural fuzzy network is proposed for nonlinear soft-sensing modeling of a chemical process. It is a feedforward multiplayer network and learns in two main phases. The proposed network was applied to a practical application of modeling the octane number of a continuous reforming plant. Results show that it possesses better generalization ability and simple model structure, and can improve octane rating modeling. A better scheme. Online quality control requires product quality measurements that often are either unavailable online or have long time delays. Soft sensing techniques are attractive and efficient methods for predicting such quality variables.1

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