1 |
Hossain, K.M.A. and Lachemi, M. (2006), "Performance of volcanic ash and pumice based blended cement concrete in mixed sulfate environment", Cement Concrete Res., 36(6), 1123-1133.
DOI
|
2 |
Inan, G., Goktepe, A.B., Ramyar, K. and Sezer, A. (2007), "Prediction of sulfate expansion of PC mortar using adaptive neuro-fuzzy methodology", Build. Environ., 42(3), 1264-1269.
DOI
|
3 |
Irassar, E.F., Bonavetti, V.L. and Gonzalez, M. (2003), "Microstructural study of sulfate attack on ordinary and limestone Portland cements at ambient temperature", Cement Concrete Res., 33(1), 31-41.
DOI
|
4 |
Irassar, E.F., Bonavetti, V.L., Trezza, M.A. and Gonzalez, M.A. (2005), "Thaumasite formation in limestone filler cements exposed to sodium sulphate solution at 20C", Cement Concrete Compos., 27(1), 77-84.
DOI
|
5 |
Kalousek, G.L., Porter, L.C. and Benton, E.J. (1972), "Concrete for long-time service in sulfate environment", Cement Concrete Res., 2(1), 79-89.
DOI
|
6 |
Kecman, V. (2001), "Learning and soft computing: Support vector machines, neural networks, and fuzzy logic models", MIT Press.
|
7 |
Kilic, A., Atis, C.D., Yasar, E. and Ozcan, F. (2003), "Highstrength lightweight concrete made with scoria aggregate containing mineral admixtures", Cement Concrete Res., 33(10), 1595-1599.
DOI
|
8 |
Hossain, K.M.A. (1999), "Performance of volcanic ash concrete in marine environment", Proceedings of the 24th OWICS Conference, Singapore, August.
|
9 |
Kosmatka, S.H. and Panarese, W.C. (2002), "Design and control of concrete mixtures", Skokie, IL: Portland Cement Assoc., 5420, 60077-1083.
|
10 |
Lee, J.J., Kim, D.K., Chang, S.K. and Lee, J.H. (2007), "Application of support vector regression for the prediction of concrete strength", Comput. Concrete, 4, 299-316.
DOI
|
11 |
Lee, S.T., Hooton, R.D., Jung, H.S., Park, D.H. and Choi, C.S. (2008), "Effect of limestone filler on the deterioration of mortars and pastes exposed to sulfate solutions at ambient temperature", Cement Concrete Res., 38(1), 68-76.
DOI
|
12 |
Lee, S.T., Moon, H.Y. and Swamy, R.N. (2005), "Sulfate attack and role of silica fume in resisting strength loss", Cement Concrete Compos., 27(1), 65-76.
DOI
|
13 |
Manual FIP (1983), FIP Manual of Lightweight Aggregate Concrete, Surrey University Press, London, U.K.
|
14 |
Mehta, P.K. (1983), "Mechanism of sulfate attack on Portland cement concrete-another look", Cement Concrete Res., 13(3), 401-406.
DOI
|
15 |
Moon, H.Y., Lee, S.T. and Kim, S.S. (2003), "Sulphate resistance of silica fume blended mortars exposed to various sulphate solutions", Can. J. Civil Eng., 30(4), 625-636.
DOI
|
16 |
Naik, T.R., Singh, S.S. and Hossain, M.M. (1996), "Enhancement in mechanical properties of concrete due to blended ash", Cement Concrete Res., 26(1), 49-54.
DOI
|
17 |
Nazari, A. and Riahi, S. (2011), "Computer-aided design of the effects of nanoparticles on split tensile strength and water permeability of high strength concrete", Mater. Des., 32(7), 3966-3979.
DOI
|
18 |
Ouyang, C., Nanni, A. and Chang, W.F. (1988), "Internal and external sources of sulfate ions in Portland cement mortar: Two types of chemical attack", Cement Concrete Res., 18(5), 699-709.
DOI
|
19 |
Ozcan, F. (2012), "Gene expression programming based formulations for splitting tensile strength of concrete", Constr. Build. Mater., 26(1), 404-410.
DOI
|
20 |
Plowman, C. and Cabrera, J.G. (1996), "The use of fly ash to improve the sulphate resistance of concrete", Waste Manage., 16(1), 145-149.
DOI
|
21 |
Akoz, F., Turker, F., Koral, S. and Yuzer, N. (1999), "Effects of raised temperature of sulfate solutions on the sulfate resistance of mortars with and without silica fume", Cement Concrete Res., 29(4), 537-544.
DOI
|
22 |
ACI 201.2R-77 (1977), Guide to Durable Concrete.
|
23 |
ACI 225R-85 (1985), Guide to the Selection and Use of Hydraulic Cements.
|
24 |
Akoz, F., Turker, F., Koral, S. and Yuzer, N. (1995), "Effects of sodium sulfate concentration on the sulfate resistance of mortars with and without silica fume", Cement Concrete Res., 25(6), 1360-1368.
DOI
|
25 |
Saridemir, M., Topcu, I.B., Ozcan, F. and Severcan, M.H. (2009), "Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic", Constr. Build. Mater., 23(3), 1279-1286.
DOI
|
26 |
Rankovic, V., Grujovic, N., Divac, D. and Milivojevic, N. (2014), "Development of support vector regression identification model for prediction of dam structural behavior", Struct. Safety, 48, 33-39.
DOI
|
27 |
Rasheeduzzafar Al-Amoudi, O.S.B., Abduljauwad, S.N. and Maslehuddin, M. (1994), "Magnesium-sodium sulfate attack in plain and blended cements", J. Mater. Civil Eng., 6(2), 201-222.
DOI
|
28 |
Sahmaran, M., Erdem, T.K. and Yaman, I.O. (2007), "Sulfate resistance of plain and blended cements exposed to wettingdrying and heating-cooling environments", Constr. Build. Mater., 21(8), 1771-1778.
DOI
|
29 |
Shafigh, P., Alengaram, U.J., Mahmud, H.B. and Jumaat, M.Z. (2013), "Engineering properties of oil palm shell lightweight concrete containing fly ash", Mater. Des., 49, 613-621.
DOI
|
30 |
Shannag, M.J. and Shaia, H.A. (2003), "Sulfate resistance of highperformance concrete", Cement Concrete Compos., 25(3), 363-369.
DOI
|
31 |
Shi, X.C. and Dong, Y.F. (2011), "Support vector machine applied to prediction strength of cement in artificial intelligence", Proceedings of the 2nd International Conference on Management Science and Electronic Commerce, China, August.
|
32 |
Sobhani, J., Najimi, M., Pourkhorshidi, A.R. and Parhizkar, T. (2010), "Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models", Constr. Build. Mater., 24(5), 709-718.
DOI
|
33 |
Al-Noury, S.I., Mirza, W.H. and Huq, S. (1990), "Density and strength characteristics of lightweight mortar", Cement Concrete Compos., 12(2), 79-86.
DOI
|
34 |
Al-Amoudi, O.S.B. (1998), "Sulfate attack and reinforcement corrosion in plain and blended cements exposed to sulfate environments", Build. Environ., 33(1), 53-61.
DOI
|
35 |
Al-Amoudi, O.S.B., Maslehuddin, M. and Saadi, M.M. (1995), "Effect of magnesium sulfate and sodium sulfate on the durability performance of plain and blended cements", ACI Mater. J., 92(1), 15-24.
|
36 |
Al-Amoudi, O.S.B., Rasheeduzzafar, M.M. and Abduljauwad, S.N. (1994), "Influence of chloride ions on sulphate deterioration in plain and blended cements", Mag. Concrete Res., 46(167), 113-123.
DOI
|
37 |
Topcu, I.B. and Saridemir, M. (2007), "Prediction of properties of waste AAC aggregate concrete using artificial neural network", Comput. Mater. Sci., 41(1), 117-125.
DOI
|
38 |
Sonebi, M., Cevik, A., Grunewald, S. and Walraven, J. (2016), "Modelling the fresh properties of self-compacting concrete using support vector machine approach", Constr. Build. Mater., 106, 55-64.
DOI
|
39 |
Stark, D. (1980), Longtime Study of Concrete Durability in Sulfate Soils Sulfate Resistance of Concrete SP-77, American Concrete Institute, U.S.A.
|
40 |
Taylor, H.F. (1997), Cement Chemistry, Thomas Telford.
|
41 |
Topcu, I.B. and Saridemir, M. (2008a), "Prediction of mechanical properties of recycled aggregate concretes containing silica fume using artificial neural networks and fuzzy logic", Comput. Mater. Sci., 42(1), 74-82.
DOI
|
42 |
Topcu, I.B. and Saridemir, M. (2008b), "Prediction of rubberized mortar properties using artificial neural network and fuzzy logic", J. Mater. Proc. Technol., 199(1), 108-118.
DOI
|
43 |
Bilim, C., Atis, C.D., Tanyildizi, H. and Karahan, O. (2009), "Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network", Adv. Eng. Software, 40(5), 334-340.
DOI
|
44 |
Altun, F., Kisi, O. and Aydin, K. (2008), "Predicting the compressive strength of steel fiber added lightweight concrete using neural network", Comput. Mater. Sci., 42(2), 259-265.
DOI
|
45 |
ASTM C 618 (2012), Standard Specification for Coal Fly Ash and Raw or Calcined Natural Pozzolan for Use in Concrete.
|
46 |
ASTM C1012 (2004), Standard Test Method for Length Change of Hydraulic-Cement Mortars Exposed to a Sulfate Solution.
|
47 |
Vapnik, V. (1995), The Nature of Statistical Learning Theory, Springer Berlag, New York, U.S.A.
|
48 |
Tsivilis, S., Kakali, G., Skaropoulou, A., Sharp, J.H. and Swamy, R.N. (2003), "Use of mineral admixtures to prevent thaumasite formation in limestone cement mortar", Cement Concrete Compos., 25(8), 969-976.
DOI
|
49 |
Turker, F., Akoz, F., Koral, S. and Yuzer, N. (1997), "Effects of magnesium sulfate concentration on the sulfate resistance of mortars with and without silica fume", Cement Concrete Res., 27(2), 205-214.
DOI
|
50 |
Uysal, M. and Tanyildizi, H. (2011), "Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network", Constr. Build. Mater., 25(11), 4105-4111.
DOI
|
51 |
Spratt, B.H. (1974), "The structural use of lightweight aggregate cement mortar", Cement, Cement Mortar Assoc., 22, 57-63.
|
52 |
Cohen, M.D. and Mather, B. (1991), "Sulfate attack on concrete: Research needs", Mater. J., 88(1), 62-69.
|
53 |
Binici, H., Aksogan, O., Cagatay, I.H., Tokyay, M. and Emsen, E. (2007), "The effect of particle size distribution on the properties of blended cements incorporating GGBFS and natural pozzolan (NP)", Pow. Technol., 177(3), 140-147.
DOI
|
54 |
Brown, P.W. (1981), "An evaluation of the sulfate resistance of cements in a controlled environment", Cement Concrete Res., 11(5), 719-727.
DOI
|
55 |
Chen, B.T., Chang, T.P., Shih, J.Y. and Wang, J.J. (2009), "Estimation of exposed temperature for fire-damaged concrete using support vector machine", Comput. Mater. Sci., 44(3), 913-920.
DOI
|
56 |
Cover, T.M. (1965), "Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition", Electr. Comput. IEEE Transac., 3, 326-334.
|
57 |
Demir, F. (2008), "Prediction of elastic modulus of normal and high strength concrete by artificial neural networks", Constr. Build. Mater., 22(7), 1428-1435.
DOI
|
58 |
Wee, T.H., Suryavanshi, A.K., Wong, S.F. and Rahman, A.K.M.A. (2000), "Sulfate resistance of concrete containing mineral admixtures", ACI Mater. J., 97(5), 536-549.
|
59 |
Vuk, T., Gabrovsek, R. and Kaucic, V. (2002), "The influence of mineral admixtures on sulfate resistance of limestone cement pastes aged in cold solution", Cement Concrete Res., 32(6), 943-948.
DOI
|
60 |
Wang, Y.R., Yu, C.Y. and Chan, H.H. (2012), "Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models", J. Proj. Manage., 30(4), 470-478.
|
61 |
Yeh, I.C. (2007), "Modeling slump flow of concrete using secondorder regressions and artificial neural networks", Cement Concrete Compos., 29(6), 474-480.
DOI
|
62 |
Wilson, C. (1954), "Cement mortar ship resists sea water thirtyfour years", Cement Mort., 62, 5-12.
|
63 |
Wong, G.S. and Poole, T.S. (1987), "The effect of pozzolans and slags on the sulfate resistance of hydraulic cement mortars", Spec. Publ., 100, 2121-2134.
|
64 |
Yan, K. and Shi, C. (2010), "Prediction of elastic modulus of normal and high strength concrete by support vector machine", Constr. Build. Mater., 24(8), 1479-1485.
DOI
|
65 |
Yu, Q.L., Spiesz, P. and Brouwers, H.J.H. (2013), "Development of cement-based lightweight composites-part 1: Mix design methodology and hardened properties", Cement Concrete Compos., 44, 17-29.
DOI
|
66 |
Yuvaraj, P., Murthy, A.R., Iyer, N.R., Sekar, S.K. and Samui, P. (2013), "Support vector regression based models to predict fracture characteristics of high strength and ultra high strength concrete beams", Eng. Fract. Mech., 98, 29-43.
DOI
|
67 |
Zarandi, M.F., Turksen, I.B., Sobhani, J. and Ramezanianpour, A.A. (2008), "Fuzzy polynomial neural networks for approximation of the compressive strength of concrete", Appl. Soft Comput., 8(1), 488-498.
DOI
|
68 |
Erdem, H. (2010), "Prediction of the moment capacity of reinforced concrete slabs in fire using artificial neural networks", Adv. Eng. Software, 41(2), 270-276.
DOI
|
69 |
Duan, Z.H., Kou, S.C. and Poon, C.S. (2013), "Prediction of compressive strength of recycled aggregate concrete using artificial neural networks", Constr. Build. Mater., 40, 1200-1206.
DOI
|
70 |
Dunstan, E.R. (1980), "A possible method for identifying fly ashes that will improve the sulfate resistance of concrete", Cement Concrete Res., 10, 20-30.
|
71 |
Hanbay, D., Turkoglu, I. and Demir, Y. (2008b), "Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks", Exp. Syst. Appl., 34(2), 1038-1043.
DOI
|
72 |
Zhang, M.H. and Gjorv, O.E. (1992), "Penetration of cement paste into lightweight aggregate", Cement Concrete Res., 22(1), 47-55.
DOI
|
73 |
Zhou, Q., Wang, F. and Zhu, F. (2016), "Estimation of compressive strength of hollow concrete masonry prisms using artificial neural networks and adaptive neuro-fuzzy inference systems", Constr. Build. Mater., 125, 417-426.
DOI
|
74 |
Felekoglu, B., Ramyar, K., Tosun, K. and Musal, B. (2006), "Sulfate resistances of different types of Turkish Portland cements by selecting the appropriate test methods", Constr. Build. Mater., 20(9), 819-823.
DOI
|
75 |
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
|
76 |
Hanbay, D., Turkoglu, I. and Demir, Y. (2008a), "An expert system based on wavelet decomposition and neural network for modeling Chua's circuit", Exp. Syst. Appl., 34(4), 2278-2283.
DOI
|
77 |
Hartshorn, S.A., Swamy, R.N. and Sharp, J.H. (2001), "Engineering properties and structural implications of Portland limestone cement mortar exposed to magnesium sulphate attack", Adv. Cement Res., 13(1), 31-46.
DOI
|
78 |
Hassan, A.A., Abouhussien, A.A. and Mayo, J. (2014), "The use of silica-breccia as a supplementary cementing material in mortar and concrete", Constr. Build. Mater., 51, 321-328.
DOI
|
79 |
Haykin, S. (1994), Neural Networks, A Comprehensive Foundation College Publishing Comp. Inc.
|