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