Abstract
For the extraction of useful knowledge from recorded process operational data, several data mining algorithms are examined on a data set generated by a dynamic simulator of a debutanizer plant. Decision tree inducer can directly extract reasonable operational rules from the data-set with no previous knowledge. By integrating the feature-subset selection wrapper algorithm, Naive-Bayes classifier and nearest-neighbor classifier can also estimate the action of operation successfully.
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