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《Journal of Functional Materials》 2006-06
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The application of BP model in predicting porosity and compressive yield strength of porous NiTi alloy

LI Qiang~(1,2),YU Jing-yuan~1,MU Bai-chun~(1,2),SUN Xu-dong~1(1.College of Material & Metallurgy,Northeastern University,Shenyang 110004,China;2.College of Materials & Chemical Engineering,Liaoning Institute of Technology,Jinzhou 121001,China)  
Based on BP neutral network theory,the model has been developed for the prediction of porosity and compressive yield strength of porous NiTi shape memory alloy(SMA) prepared by thermal explosion.The results indicate that the model is capable of reproducing the effects of changes in temperature,particle size of Ti and green density on product porosity and compressive yield strength.When temperature,particle size of Ti and green porosity changed,the product properties are predicted.Good agreement between predicted and experimental data is obtained.So the model can be used in the quality control of porous NiTi SMA.By the proper adjustment of the properties,porous NiTi SMA can better match the replaced tissue.This way can improve the efficiency and reduce the cost.
【Fund】: 国家杰出青年基金资助项目(50425413);; 国家自然科学基金资助项目(50372009);; 辽宁教育厅基金资助项目(20031008)
【CateGory Index】: TB383.4
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2 XIAO Zhuohao LU Anxian LIU Shujiang YANG Zhou (College of Materials Science and Engineering,Central South University,Changsha 410083);Application of Artificial Neural Networks to Glass Composition Design[J];Materials Review;2005-06
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5 LIU Yan-xia1,GAO Xin-chen1,ZHANG Guo-ying2,GUO Huai-hong1(1.Collage of Physics,Liaoning University,Shenyang 110036,China;2.College of Physics Science and Technology,Shenyang Normal University,Shenyang 110034,China);BP Neural Networks Used in Prediction and Analyses of 3C Steel Corrosion Function[J];Journal of Materials Science and Engineering;2008-01
6 ZHANG Gang HE Xiao-min HANG Xiao-hui HUANG Yong-hui(Guangdong University of Technology Guangzhou 510006 China);Research of Application of Machine Learning Theory in Teaching Quality Evaluation[J];Journal of University of Electronic Science and Technology of China(Social Sciences Edition);2008-04
7 GAO Yan-qing,FANG Jing-cheng,ZHAO Zhi-yu,YANG Lei(College of Mechanical Engineering and Automation,Huaqiao University,Quanzhou 362021,China);Application of RBF neural network for forecasting characteristics of in-flight particles by plasma spraying[J];Journal of Functional Materials;2007-09
8 ZHAO Xiu gai (College of Computer and Information Engineering,Guangxi University,Nanning 530004,China);Model for coefficient of thermal expansion in SiO_2-Al_2O_3-CaO-Na_2O-MgO glass ceramic using artificial neural network[J];Journal of Guangxi University;2000-04
9 GUO Dong 1, WANG Yongli 1, XIA Juntao 2, LI Longtu 1, GUI Zhilun 1 (1. Department of Materials Science & Engineering, Tsinghua University, Beijing 100084; 2. School of Chemical Engineering and Materials Science, Beijing Institute of Techno;INVESTIGATION OF BaTiO_3 FORMULATION THROUGH ARTIFICIAL NEURAL NETWORK TECHNIQUE[J];Journal of The Chinese Ceramic Society;2002-03
10 ZHANG Zuotai, SAIYINBATER, LI Wenchao (Department of Physical Chemistry, University of Science and Technology Beijing, Beijing 100083, China);SYNTHESIS OF AION - TiN COMPOSITES AND OPTIMIZATION OF THE SYNTHESIS TECHNOLOGY[J];Journal of The Chinese Ceramic Society;2003-08
【Secondary References】
Chinese Journal Full-text Database 4 Hits
1 CAI Cong-zhong,WANG Gui-lian,PEI Jun-fang,ZHU Xing-jian(Department of Applied Physics,Chongqing University,Chongqing 401331,P.R.China);Prediction on the softening point of bitumen in producing by using SVR[J];Journal of Chongqing University;2011-09
2 HUANG Si-jie,CAI Cong-zhong,ZENG Qing-wen(Department of Applied Physics,Chongqing University,Chongqing 401331,China);Process parameters optimization for TiN/AlN multilayer films fabricated by pulsed laser deposition via SVR[J];Journal of Functional Materials;2013-14
3 WEN Yu-feng;CHEN Zhi-quan;TANG Peng-jie;LAI Zhang-li;School of Mathematics and Physics, Jinggangshan University;;SUPPORT VECTOR REGRESSION PREDICTION OF THE SPECIFIC HEAT CAPACITY OF FOOD[J];Journal of Jinggangshan University(Natural Science);2014-05
4 CAI Cong-zhong, WEN Yu-feng, ZHU Xing-jian, PEI Jun-fang, WANG Gui-lian, XIAO Ting-ting (Department of Applied Physics, Chongqing University, Chongqing 400044, China);Quantitative prediction of mechanical properties of 7005 Al alloys from processing parameters via support vector regression[J];The Chinese Journal of Nonferrous Metals;2010-02
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