[1]
J. Sobhani, M. Najimi, A. R. Pourkhorshidi, and T. Parhizkar,Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models, Construction and Building Materials, vol. 24, (2010) 709-718.
DOI: 10.1016/j.conbuildmat.2009.10.037
Google Scholar
[2]
ACI-211.3, Guide for selecting proportions for no-slump concrete. Farmington Hills (MI): American Concrete Institute; 2002, 2002.
Google Scholar
[3]
R. Mannonen, "Proportioning in the ready-mix industry and the benefits of a mix design program," in In: ERMCO-95, Proceedings of the XIth European Ready Mixed Concrete Congress, Istanbul, 1995, pp.177-184.
Google Scholar
[4]
J. Kasperkiewicz,Optimization of Concrete Mix Using a Spreadsheet Package, ACI Material Journal, vol. 91, (1995) 551-559.
Google Scholar
[5]
I. C. Yeh,Design of High-Performance Concrete Mixture Using Neural Networks and Nonlinear Programming, Journal of Computing in Civil Engineering, vol. 13, (1999) 36-42.
DOI: 10.1061/(asce)0887-3801(1999)13:1(36)
Google Scholar
[6]
C. J. Ke, Q. Hu, P. Jiang, and L. Zhang,Optimum Autoclaved Cement Concrete Mix Design Based on Flexural Strength, in Manufacturing Process Technology, Pts 1-5. vol. 189-193, Z. Y. Jiang, S. Q. Li, J. M. Zeng, X. P. Liao, and D. G. Yang, Eds., ed Stafa-Zurich: Trans Tech Publications Ltd, 2011, pp.676-679.
DOI: 10.4028/www.scientific.net/amr.189-193.676
Google Scholar
[7]
L. Fan, L. Zhang, and F. H. Li,Comparative study on HPC mix design methods, in High Performance Structures and Materials Engineering, Pts 1 and 2. vol. 217-218, M. Zhou, Ed., ed Stafa-Zurich: Trans Tech Publications Ltd, 2011, pp.175-180.
DOI: 10.4028/www.scientific.net/amr.217-218.175
Google Scholar
[8]
Y. D. Wang and X. C. Fan,Experimental Research on Physical and Mechanical Properties of Steel Fiber High-strength Concrete, in Advances in Building Materials, Pts 1-3. vol. 168-170, L. J. Li, Ed., ed Stafa-Zurich: Trans Tech Publications Ltd, 2011, pp.1061-1064.
DOI: 10.4028/www.scientific.net/amr.168-170.1061
Google Scholar
[9]
X. S. Song and G. Q. Xu,Optimum Study and Engineering Application of Mixing Ratio for C50 Concrete, in Advances in Building Materials, Pts 1-3. vol. 168-170, L. J. Li, Ed., ed Stafa-Zurich: Trans Tech Publications Ltd, 2011, pp.537-540.
DOI: 10.4028/www.scientific.net/amr.168-170.537
Google Scholar
[10]
R. Perera and F. B. Varona,Flexural and Shear Design of FRP Plated RC Structures Using a Genetic Algorithm, Journal of Structural Engineering, vol. 135, (2009) 1418-1429.
DOI: 10.1061/(asce)0733-9445(2009)135:11(1418)
Google Scholar
[11]
D. Goldberg, Genetic algorithms in search, optimization and machine learning. New York: Addison Wesley; 1989. New York: Addison Wesley, 1989.
Google Scholar
[12]
C. Lian, Y. Zhug, and S. Beecham,Modelling Pervious Concrete under Compression Loading - A Discrete Element Approach, in Advances in Building Materials, Pts 1-3. vol. 168-170, L. J. Li, Ed., ed Stafa-Zurich: Trans Tech Publications Ltd, 2011, pp.1590-1600.
DOI: 10.4028/www.scientific.net/amr.168-170.1590
Google Scholar
[13]
Y. I-Cheng,Computer-aided design for optimum concrete mixtures, Cement and Concrete Composites, vol. 29, (2007) 193-202.
DOI: 10.1016/j.cemconcomp.2006.11.001
Google Scholar