DocumentCode
3305049
Title
Prediction of Material Mechanical Properties with Support Vector Machine
Author
Tang, Jia-li ; Cai, Qiu-ru ; Liu, Yi-Jun
fYear
2010
fDate
24-25 April 2010
Firstpage
592
Lastpage
595
Abstract
Predicting model which refers to mechanical properties with material composition and techniques can be founded to reduce test times, increase efficiency and realize the optimization of process. This paper proposes to apply the Support Vector Machine to set up the nonlinear mapping from influence factors of material performances to mechanical properties. Taking the wheat straw-reinforced composite for instance, the prediction model based on support vector machine has been built. Besides, the model is used to optimize process parameters of injection molding and find the range of best parameters. The simulation result shows the founded model has preferable learning and generalization capabilities, which performs effectively in predicting mechanical properties. Therefore it is feasible to optimize process parameters and the technology is worthy to be applied and spread in the research of material performance.
Keywords
Artificial neural networks; Composite materials; Injection molding; Kernel; Machine learning; Machine learning algorithms; Materials testing; Mechanical factors; Predictive models; Support vector machines; Support Vector Machine; material mechanical properties; predicting model;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location
Kaifeng, China
Print_ISBN
978-1-4244-6595-8
Electronic_ISBN
978-1-4244-6596-5
Type
conf
DOI
10.1109/MVHI.2010.58
Filename
5532566
Link To Document