Inference mechanism for polymer processing using rough-neuro fuzzy network
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The databases of real world contains a huge volume of data and among them there are hidden piles of interesting relations that are actually very hard to find out. The knowledge discovery databases (KDD) appear as a possible solution to find out such relations aiming at converting information into knowledge. However, not a data presented in the bases are useful to a KDD. Usually, data are processed before being presented to a KDD aiming at reducing the amount of data and also at selecting more relevant data to be used by the system. The purpose of this paper is to describe a validation methodology, through of a MLP neural network, to the knowledge discovered by a Hybrid Architecture composed by Rough Sets Theory used to pre-processing the data to be presented to Self-Organizing Maps neural network, which data cluster.