Application of generalized regression neural network in prediction of cement properties

2010 International Conference on Computer Design and Applications, ICCDA 2010

Volumn 2, Issue , 2010, Pages

  Ren, Shuxia ^a   Yang, Dan ^b   Ji, Fengqiu ^a   Tian, Xiushu ^a  

^a SHIJIAZHUANG TIEDAO UNIVERSITY   (China)

^b Shijiazhuang People's Armed Police Command College ^*  (China)

Author keywords

Compressive strength; Generalized regression neural network; Hydration heat

Indexed keywords

BP NEURAL NETWORKS; CEMENT PROPERTIES; CHEMICAL COMPOSITIONS; GENERALIZED REGRESSION NEURAL NETWORK; GENERALIZED REGRESSION NEURAL NETWORKS; HYDRATION HEAT; MAXIMUM RELATIVE ERRORS; MODELLING METHOD; TRAINING SPEED;

CEMENTS; COMPRESSIVE STRENGTH; COMPUTER APPLICATIONS; HYDRATION; REGRESSION ANALYSIS;

NEURAL NETWORKS;

EID: 77955874355     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCDA.2010.5541402     Document Type: Conference Paper

References (8)

1. C.E. de Siquera Tango, "An extrapolation method for compressivestrength prediction of hydraulic cement products", Cem Concr Res,vol. 28 , pp. 969-983, July 1998.
2. S. Tsivilis, G. Parissakis, "A mathematical-model for the prediction of cement strength", Cem Concr Res , vol.25, pp. 9-14. January 1995
3. Adil Baykasoglu, Tukay Dereli, Serkan Tanis, "Prediction of cement strength using soft computing techniques", Cem. Concr, Res., vol. 34, pp. 2083-2090, 11 ,2004
4. Abdulhamit Subasi, Ahmet Serdar Yilmaz, Hanif,Binici, "Prediction of early heat of hydration of plain and blended cements using neurofuzzy modelling techniques", Expert Systems with Applications, vol.36 , pp. 4940-4950, April 2009
5. Anka Ilc, Goran Turk, Franci Kavčič, Gregor Trtnik, "New numerical procedure for the prediction of temperature development in early age concrete structures", Automation in Construction, vol.18, pp. 849-855, October, 2009
6. Jiao Zhicheng. Theoryof Neural Network System. Xi an: Xi'an Electronic Science and Technology University Press. 1995.
7. Dirk Tomandl, Andreas ,Schober "A Modified General Regression Neural Network (MGRNN) with new, efficient training algorithms as a robust 'black box'-tool for data analysis", Neural Networks, vol. 14 , pp. 1023-1034, October 2001.
8. Ge Zhexue, Sun Zhiqiang. Neural Network Theory and realization of MATLAB R2007 [M]. Beijing: Electronics Industry Press, 2007.