Application of data mining techniques in predicting the behaviour of composite joints
Authors: Kia, S.S., Noroozi, S., Carse, B. and Vinney, J.
Volume: 82
ISBN: 9781905088058
Abstract:The evaluation and prediction of the failure probability and safety levels of composite components and structures is of extreme importance in structural design and manufacturing. A new application of data mining techniques for predicting the behaviour of pin-loaded composite joints is presented. The proposed system consists of combining data mining and soft computing techniques such as classification and clustering with fuzzy logic. By using these techniques, the relationship among different parameters such as edge distance and tensile strength of composite joints is modelled. A classification approach based on fuzzy clustering yielded the best predictive results. © Civil-Comp Press, 2005.
Source: Scopus
Application of Data Mining Techniques in Predicting the Behaviour of Composite Joints
Authors: Shrazi Kia, S., Noroozi, S., Carse, B. and Vinney, J.
Editors: Topping, B.H.V.
Pages: 47-48
Publisher: Civil-Comp Press
Place of Publication: Stirling
Source: Manual
Preferred by: John Vinney and Siamak Noroozi