Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
Deformation Decision Knowledge Extraction of FWP Processing Based on RS and Entropy
verfasst von : Yaohua Deng, Guixiong Liu, Liming Wu
Erschienen in: Emerging Computation and Information teChnologies for Education
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Deformation decisions knowledge extraction based on RS and entropy reduction is proposed for FWP processing which processing deformation factors is complex and difficult to extract. Decision table of processing deformation which takes FWP processing deformation factors as conditional attribute and processing deformation level as decision attribute. Changes in the level of mutual information as a condition attribute importance to the decision attribute evaluation, when the greater the change in the conditions the more important attribute for decision attribute. In Application examples, there are 13 conditional attribute in decision table, in accordance with Pawlak reduction methods and genetic reduction algorithm to extract 5 highest impact factors, 4 highest impact factors for FWP processing deformation decision are extracted using entropy reduction method. Prediction error of Entropy Reduction Method is 32.58% less than Pawlak’s reduction method, and 21.45% less than Genetic reduction algorithm.