Partially stabilised zirconia stability prediction based on opposite degree algorithm for safety engineering. (May 2015)

• Record Type: Journal Article
• Authors: Zhang, G.; Yue, X.-G.; Li, F.; Zhao, S.-L.
• Is Part Of: Materials research innovations. Volume 19(2015)Supplement 5
• Page Start: S5-671
• Page End: S5-673
• Publication Date: 2015-05
• Subjects: Partially stabilised zirconia -- Stability -- Opposite degree algorithm -- BP neural network -- Safety engineering; Materials -- Research -- Periodicals; Matériaux -- Recherche -- Périodiques; 620.1105
• DOI: 10.1179/1432891714Z.0000000001173
• Languages: English
• ISSNs: 1432-8917

Abstract

Abstract : In order to predict the partially stabilised zirconia stability, relevant prediction methods for partially stabilised zirconia stability are discussed; opposite degree algorithm is used to predict the partially stabilised zirconia stability. The prediction operator steps are designed. Opposite degree algorithm is based on prior values, posterior values and the opposite degrees between the training data and the testing data. In order to compare the prediction results based on various algorithms, back propagation neural network method is used for partially stabilising zirconia stability. The prediction results show that the opposite degree algorithm is better than back propagation neural network. Opposite degree algorithm is an effective method for partially stabilised zirconia stability prediction. Opposite degree algorithm can be applied in safety engineering for more aspects.