Application of generalized regression neural network in prediction of cement properties

@article{Ren2010ApplicationOG,
  title={Application of generalized regression neural network in prediction of cement properties},
  author={Shuxia Ren and Dan Yang and Fengqiu Ji and Xiushu Tian},
  journal={2010 International Conference On Computer Design and Applications},
  year={2010},
  volume={2},
  pages={V2-385-V2-388}
}
Different modelling methods based on neural networks have become popular and been widely used in a great variety of fields. The properties of cements were predicted by neural network according to their chemical compositions, fineness, and other factors in this paper. The results showed that generalized regression neural network (GRNN) has higher accuracy and faster training speed compared with BP neural network. The maximum relative errors of the hydration heat and compressive strength… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-8 of 8 references

Trtnik, "New numerical procedure for the prediction of temperature development in early age concrete structures

  • Anka IIc, Goran Turk, Franci Kavcic, Gregor
  • Automation in Construction,
  • 2009

Prediction of cement strength using soft computing techniques

  • Adil Baykasoglu, Tukay Dereli, Serkan Tams
  • Cern. Concr, Res.,
  • 2004

Prediction of cement strength using soft computing techniques " , Cern

  • Adil Baykasoglu, Tukay Dereli, Serkan Tams
  • 2004

Schober "A Modified General Regression Neural Network (MGRNN) with new, efficient training algorithms as a robust 'black box'-tool for data analysis

  • Dirk Tomandl, Andreas
  • Neural Networks,
  • 2001

Siquera Tango, "An extrapolation method for compressivestrength prediction of hydraulic cement products

  • c.E. de
  • Cern Concr Res,vol
  • 1998

Parissakis, "A mathematical-model for the prediction of cement strength

  • G. S. Tsivilis
  • Cern Concr Res ,
  • 1995

Theoryof Neural Network System. Xi an: Xi'an Electronic Science and Technology

  • Jiao Zhicheng
  • 1995

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