1 |
Mohammed, A., Mashrei, N.A. and Turki, Y. (2010), "Neural networks model and adaptive neuro-fuzzy inference system for predicting the moment capacity of ferrocement members", Eng. Struct., 32(6), 1723-1734.
DOI
|
2 |
Murat, P. and Aimin, X. (2004), "Value-added utilsation of waste glass in concrete", Cement Concrete Res., 34(1), 81-89.
DOI
|
3 |
Naik, U. and Kute, S. (2013), "Span-to-depth ratio effect on shear strength of steel fiber reinforced high-strength concrete deep beams using ANN method", J. Adv. Struct. Eng., 1-12.
|
4 |
Ilker, B.T. and Mustafa, S. (2008), "Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic", Comput. Mater. Sci., 41(3), 305-311.
DOI
|
5 |
Jin, Z.H. and Zhang, L. (2006), Accelerated Test Method by Binary Regression for Cement Strength, Testing Centre of Sinohydro Engineering Bureau 15 Co. Ltd, Shannxi, China.
|
6 |
Jordi, M. (2011), "Mean absolute percentage error and bias in economic forecasting", Eco. Lett., 113(3), 259-262.
DOI
|
7 |
Kar, A., Ray, I., Unnikrishnan, A. and Halabe, U.B. (2016), "Prediction models for compressive strength of concrete with alkali-activated binders", Comput. Concrete, 17(4), 523-539.
DOI
|
8 |
Kong, L., Chen, X. and Du, Y. (2016), "Evaluation of the effect of aggregate on concrete permeability using grey correlation analysis and ANN", Comput. Concrete, 17(5), 613-628.
DOI
|
9 |
Khan, S.U., Ayub, T. and Rafeeqi, S.F.A. (2013), "Prediction of compressive strength of plain concrete confined with ferrocement using artificial neural network (ANN) and comparison with existing mathematical models", Am. J. Civil Eng. Arch., 1(1), 7-14.
DOI
|
10 |
Kisi, O. (2007), "Streamflow forecasting using different artificial neural network algorithms", J. Hydrol. Eng., 12(5), 532-539.
DOI
|
11 |
Kuo, W.T. and Shu, C.Y. (2014), "Application of high-temperature rapid catalytic technology to forecast the volumetric stability behavior of containing steel slag mixtures", Constr. Build. Mater., 50, 463-470.
DOI
|
12 |
Kuo, W.T. and Shu, C.Y. (2015), "Expansion behavior of lowstrength steel slag mortar during high-temperature catalysis", Comput. Concrete, 16(2), 261-274.
DOI
|
13 |
Kuo, W.T., Shu, C.Y. and Han, Y.W. (2014), "Electric arc furnace oxidizing slag mortar with volume stability for rapid detection", Constr. Build. Mater., 53, 635-641.
DOI
|
14 |
Luo, Y.H., Han, Y.F. and Gao, Z.G. (2005), "Curve-fitting of concrete's rebound strength testing based on the neural network", Res. Appl. Build. Mater., 3, 7-9.
|
15 |
Lewis, C.D. (1982), Industrial and Business Forecasting Method, Butterworth Scientific Publishers, London, U.K.
|
16 |
Liu, J., Li, H. and He, C. (2011), "Predicting the compressive strength of concrete using rebound method and artificial neural network", ICIC Expr. Lett., 5(4), 1115-1120.
|
17 |
Lun, Y., Zhou, M., Cai, X. and Xu, F. (2008), "Methods for improving volume stability of steel slag as fine aggregate", J. Wuhan Univ. Tech-Mater. Sci. Ed., 23(5), 737-742.
DOI
|
18 |
Mahmoud, A. (2012), "Laboratory studies to investigate the properties of cir mixes containing steel slag as a substitute for virgin aggregates", Constr. Build. Mater., 26(1), 475-480.
DOI
|
19 |
Mashrei, M.A., Abdulrazzaq, N., Abdalla, T.Y. and Rahman, M.S. (2010), "Neural networks model and adaptive neuro-fuzzy inference system for predicting the moment capacity of ferrocement members", Eng. Str., 32(6), 1723-1734.
DOI
|
20 |
Maslehuddin, M., Sharif, A.M., Shameem, M., Ibrahim, M. and Barry, M.S. (2003), "Comparison of properties of steel slag and crushed limestone aggregate concretes", Constr. Build. Mater., 17(2), 105-112.
DOI
|
21 |
Shen, W., Zhou, M. and Ma, W. (2009), "Investigation on the application steel slag-fly ash-phosphogypsum solidified material as road base material", Hazard. Mater., 164(1), 99-104.
DOI
|
22 |
Qasrawi, H. (2009), "Use of low CaO unprocessed steel slag in concrete as fine aggregate", Constr. Build. Mater., 23(2), 1118-1125.
DOI
|
23 |
Sakthivel, P.B., Alagumurthi, A. and Modeling, N. (2016), "Modeling and prediction of flexural strength of hybrid mesh and fiber reinforced cement-based composites using artificial neural network (ANN)", J. Geomater., 10(1), 1623-1635.
|
24 |
Shen, D.H., Wu, C.M. and Du, J.C. (2009), "Laboratory investigation of basic oxygen furnace slag for substitution of aggregate in porous asphalt mixture", Constr. Build. Mater., 23(1), 453-461.
DOI
|
25 |
Shi, J.P. and Li, X. (2010), "Build 28d compressive strength forecasting equation by curve fitting", Cement Eng., 4, 77-78.
|
26 |
Shu, C.Y., Kuo, W.T. and Juang, C.U. (2016), "Analytical model of expansion for electric arc furnace oxidizing slag-containing concrete", Comput. Concrete, 18(5), 937-950.
DOI
|
27 |
Silva, R.V., Brito, J. and Dhir, R.K. (2013), "Prediction of compressive strength of recycled aggregate concrete using artificial neural networks", Constr. Build. Mater., 40, 1200-1206.
DOI
|
28 |
US Federal Environment Protection Agency (2010), Use of Recycled Industrial Materials in Roadways.
|
29 |
Silva, R.V., Brito, J. and Dhir, R.K. (2015), "Prediction of the shrinkage behavior of recycled aggregate concrete: A review", Constr. Build. Mater., 77, 327-339.
DOI
|
30 |
Tavakoli, H.R., Lotfi, O.O., Falahtabar, S.M. and Soleimani, S.S. (2014), "Prediction of combined effects of fibers and nanosilica on the mechanical properties of self-compacting concrete using artificial neural network", Lat. Am. J. Sol. Str., 11(11), 1906-1923.
DOI
|
31 |
Wang, C.C., Wang, H.Y. and Huang, C. (2014), "Predictive models of hardened mechanical properties of waste LCD glass concrete", Comput. Concrete, 14(5), 577-597.
DOI
|
32 |
Aggarwal, P., Aggarwal, Y., Siddique, R., Gupta, S. and Garg, H. (2013), "Fuzzy logic modeling of compressive strength of highstrength concrete (HSC) with supplementary cementitious material", J. Sustain. Cement Base. Mater., 2(2), 1-16.
DOI
|
33 |
Alexandre, J. and Boudonnet, J.Y. (1993), "Les laitiers d'acierie LD et leurs utilisations routieres", Laitiers Siderurgiques, 75, 57-62.
|
34 |
Atici, U. (2011), "Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network", Exp. Syst. Appl., 38(8), 9609-9618.
DOI
|
35 |
Wang, B.X., Man, T.N. and Jin, H.N. (2015), "Prediction of expansion behavior of self-stressing concrete by artificial neural networks and fuzzy inference systems", Constr. Build. Mater., 84, 184-191.
DOI
|
36 |
Wang, C.C., Chen T.T., Wang, H.Y. and Huang, C. (2014), "A predictive model for compressive strength of waste LCD glass concrete by nonlinear-multivariate regression", Comput. Concrete, 13(4), 531-545.
DOI
|
37 |
Wang, G. (2010), "Determination of the expansion force of coarse steel slag aggregate", Constr. Build. Mater., 24(10), 1961-1966.
DOI
|
38 |
Wang, G., Wang, Y. and Gao, Z. (2010), "Use of steel slag as a granular material: Volume expansion prediction and usability criteria", J. Hazard. Mater., 184(1), 555-560.
DOI
|
39 |
Beshears and Tutumluer. (2013), Reclaimed Asphalt Pavement with Steel Slag Aggregate, TR NEWS 288, 46-47, September-October.
|
40 |
Wang, W.C., Liu, C.C., Lee, C. and Yu, S.K. (2011), "Preliminary research of expansion problem and treated method of using slag as aggregate of concrete", Proceedings of the TCI Conference on Concrete Engineering.
|
41 |
Chithra, S., Senthil Kumar, S.R.R., Chinnaraju, K. and Alfin Ashmita, F. (2016), "A comparative study on the compressive strength prediction models for high performance concrete containing nano silica and copper slag using regression analysis and artificial neural networks", Constr. Build. Mater., 114, 528-535.
DOI
|
42 |
Deshpande, N., Londhe, S. and Kulkarni, S. (2014), "Modeling compressive strength of recycled aggregate concrete by artificial neural network", model tree and non-linear regression, J. Sustain. Built Environ., 3(2), 187-198.
DOI
|
43 |
Deshpande, N., Londhe, S. and Kulkarni, S.S. (2013), "Modelling compressive strength of recycled aggregate concrete using neural networks and regression", Concrete Res. Lett., 4(2), 580-590.
|
44 |
Huang, K.J., Deng, M., Shen, Y.Q. and Mo, L.W. (2010), "Failure analysis of early age cracking of paving concrete in donghai country", J. Wuhan Univ. Tech-Mater. Sci. Ed., 32(5), 62-66.
|
45 |
Gulbandilar, E. and Kocak, Y. (2016), "Application of expert systems in prediction of flexural strength of cement mortars", Comput. Concrete, 18(1), 1-16.
DOI
|
46 |
Hagan, D.I. (2004), Neural Network Design, Thomson.
|
47 |
Han, Y.M., Jung, H.Y., Seong, S.K. (2002), "A fundamental study on the steel slag aggregate concrete", Geosyst. Eng., 5(2), 38-45.
DOI
|
48 |
Huang, Q. (2014), "Add prediction mode of waste LCD glass concrete elaboration mechanics and engineering", Ph.D. Dissertation, National Kaohsiung Institute of Technology in Civil Engineering and Disaster Prevention University of Applied Sciences, Taiwan.
|
49 |
Hwang, C.L. (2010), High Performance Concrete Theory and Practice, Taipei, Zhan Shi, Taiwan.
|