Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

10.1007/BF00058655

10.1023/A:1017934522171

10.1023/A:1008640732416

Chang C. Z. (1997). Research on the mix proportion of high flowing eugenic concrete Chung Hua Univ. Hsin Chu Taiwan.

Chang C.-C. and Lin C.-J. (2001). LIBSVM : A library for support vector machines [Computer software]. 〈http://www.csie.ntu.edu.tw/~cjlin/libsvm〉

10.1080/02533839.1996.9677830

Chung F. C. (1995). Study on characteristic of coarse aggregate in high-performance concrete National Taiwan Univ. of Science and Technology Taipei Taiwan.

10.1061/(ASCE)0887-3801(2001)15:3(208)

10.1023/A:1013685603443

Euro-International Concrete Committee and International Federation for Prestressing (CEB-FIP). (1994). “Application of high performance concrete.” Rep. of CEB-FIP working group on HS/HPC Int. Federation for Structural Concrete Lausanne Switzerland 69.

Fan D. Chan P. and Stolfo S. (1996). “A comparative evaluation of combiner and stacked generalization.” AAAI 1996 Workshop on Integrating Multiple Learned Models for Improving and Scaling Machine Learning Algorithms Association for the Advancement of Artificial Intelligence Menlo Park CA 40–46.

10.1016/j.asoc.2007.02.010

10.1214/aos/1013203451

Giaccio G., 1992, High-strength concretes incorporating different coarse aggregates, ACI Mater. J., 89, 242

Gjorv O. E., 1990, Effect of condensed silica fume on the steel-concrete bond, ACI Mater. J., 87, 573

10.1061/(ASCE)0899-1561(2006)18:3(462)

10.1111/j.1467-8667.1994.tb00369.x

10.1016/S0958-9465(98)00002-X

Hwang G. E. (1991). A study on blast furnace slag concrete National Chiao Tung Univ. Hsin Chu Taiwan.

Hwang T. S. (1966). Compressive strength of blast furnace slag concrete National Chiao Tung Univ. Hsin Chu Taiwan.

Ian W. H., 1999, Data mining: Practical machine learning tools and techniques with Java implementations

Iba W. and Langley P. (1992). “Induction of one-level decision trees.” Proc. Ninth Int. Machine Learning Conf. Int. Machine Learning Society Princeton NJ.

10.1109/21.256541

10.1061/(ASCE)0887-3801(1995)9:4(279)

Kohavi R. (1995). “A study of cross-validation and bootstrap for accuracy estimation and model selection.” Proc. 14th Int. Joint Conf. on Artificial Intelligence Morgan Kaufmann San Francisco 1137–1143.

Langley W. S., 1989, Structural concrete incorporating high volumes of ASTM Class F fly ash, ACI Mater. J., 86, 507

Lee C. F. (1994). A study on dry shrinkage and creep property of HPC National Taiwan Univ. of Science and Technology Taipei Taiwan.

10.1016/j.commatsci.2008.07.012

Lessard M., 1993, Testing high-strength concrete compressive strength, ACI Mater. J., 90, 303

Lin F. Y. (1994). Mixture proportion and quality of HPC National Taiwan Univ. of Science and Technology Taipei Taiwan.

Mo H. L. (1995). A study on high performance concrete National Taiwan Univ. of Science and Technology Taipei Taiwan.

Mostofi D., 1995, HPC strength prediction using artificial neural network, J. Comput. Civ. Eng., 9, 44

Oh J., 1999, Applications of neural networks for proportioning of concrete mixes, ACI Mater. J., 96, 51

Oluokun F. A., 1994, Fly ash concrete mix design and the water-cement ratio law, ACI Mater. J., 91, 362

Pal M. and Mather P. M. (2003). “Support vector classifiers for land cover classification.” Proc. 6th Annual Int. Conf. and Exhibition MapIndia Map India Noida India 28–31.

Popovics S., 1990, Analysis of the concrete strength versus water-cement ratio relationship, ACI Mater. J., 87, 517

10.1016/j.commatsci.2004.11.001

10.1023/B:STCO.0000035301.49549.88

SPSS Clementine version 12 [Computer software]. IBM Chicago.

10.1016/j.commatsci.2007.04.009

10.1016/j.ultras.2008.05.001

10.1007/978-1-4757-2440-0

Vapnik V. N., 1998, Statistical learning theory

10.1016/S0008-8846(98)00165-3

10.1061/(ASCE)0887-3801(1999)13:1(36)

10.1016/j.eswa.2008.07.004