1 |
Dellinghausen L.M., Gastaldini A.L.G., Vanzin F.J. and Veiga K.K. (2012), "Total shrinkage, oxygen permeability, and chloride ion penetration in concrete made with white Portland cement and blast-furnace slag", Constr. Build. Mater., 37, 652-659.
DOI
|
2 |
Demir, F. (2008), "Prediction of elastic modulus of normal and high strength concrete by artificial neural network", Constr. Build. Mater., 22(7), 1428-1435.
DOI
|
3 |
Eiras, J.N., Segovia, F., Borrachero, M.V., Monzo, J., Bonilla, M. and Paya, J. (2014), "Physical and mechanical properties of foamed Portland cement composite containing crumb rubber from worn tires", Mater. Des., 59, 550-557.
DOI
|
4 |
Gulbandilar, E. and Kocak, Y. (2013), "Prediction the effects of fly ash and silica fume on the setting time of Portland cement with fuzzy logic", Neur. Comput. Appl., 22, 1485-1491.
DOI
|
5 |
Jang, J.S.R. (1996), "Input selection for ANFIS learning, Fuzzy Systems", Proceedings of the Fifth IEEE International Conference on, New Orleans, September.
|
6 |
Komleh, H.E and Maghsoudi, A.A. (2015), "Prediction of curvature ductility factor for FRP strengthened RHSC beams using ANFIS and regression models", Comput. Concrete, 16(3), 399-414.
DOI
|
7 |
Mansouri, I. and Kisi, O. (2015), "Prediction of debonding strength for masonry elements retrofitted with FRP composites using neuro fuzzy and neural network approaches", Compos.: Part B, 70, 247-255.
DOI
|
8 |
Motamedi, S., Shamshirband, S., Petkovic, D. and Hashim, R. (2015), "Application of adaptive neuro-fuzzy technique to predict the unconfined compressive strength of PFA-sand-cement mixture", Powder Tech., 278, 278-285.
DOI
|
9 |
Ozcan, F., Atis, C.D., Karahan, O., Uncuoglu, E. and Tanyildizi, H. (2009), "Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete", Adv. Eng. Softw., 40, 856-863.
DOI
|
10 |
Parichatprecha, R. and Nimityongskul, P. (2009), "Analysis of durability of high performance concrete using artificial neural Networks", Constr. Build. Mater., 23, 910-917.
DOI
|
11 |
Sakthivel, P.B., Ravichandran, A. and Alagumurthi, N. (2016), "Modeling and pediction of flexural strength of hybrid mesh and fiber reinforced cement-based composites using Artificial Neural Network (ANN)", Int. J. Geomate, 10(1), 1623-1635.
|
12 |
Siddiquea, R. and Bennacer, R. (2012), "Use of iron and steel industry by-product (GGBS) in cement paste and mortar. Resources", Conserv. Recy., 69, 29-34.
DOI
|
13 |
Subasi, S. (2009), "Prediction of mechanical properties of cement containing class C fly ash by using artificial neural network and regression technique", Sci. Res. Essay, 4(4), 289-297.
|
14 |
Teng, S., Lim, T.Y.D. and Divsholi, B.S. (2013), "Durability and mechanical properties of high strength concrete incorporating ultra fine ground granulated blast-furnace slag", Constr. Build. Mater., 40, 875-881.
DOI
|
15 |
Topcu, İ.B. and Saridemir, M. (2008), "Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic", Comput. Mater. Sci., 41, 305-311.
DOI
|
16 |
Topcu, İ.B., Karakurt, C. and Saridemir, M. (2008), "Predicting the strength development of cements produced with different pozzolans by neural network and fuzzy logic", Mater. Des., 29(10), 1986-1991.
DOI
|
17 |
TS EN 197-1 (2012), "Cement- Part 1: Compositions and conformity criteria for common cements", Turkish Standards, Ankara, Turkey.
|
18 |
Topcu, İ.B., Saridemir, M., 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, 1279-1286.
DOI
|
19 |
Trtnik, G., Kavcic, F. and Turk, G. (2009), "Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks", Ultrasonics, 49(1), 53-60.
DOI
|
20 |
TS EN 196-1 (2009), "Methods of testing cement-Part 1: Determination of strength", Turkish Standards, Ankara, Turkey.
|
21 |
Uygunoglu, T. and Topcu, I.B. (2010), "The role of scrap rubber particles on the drying shrinkage and mechanical properties of self-consolidating mortars", Constr. Build. Mater., 24(7), 1141-1150.
DOI
|
22 |
Wang, B., Man, T. and Jin, H. (2015), "Prediction of expansion behavior of self-stressing concrete by artificial neural networks and fuzzy inference systems", Constr. Build. Mater., 84, 184-191.
DOI
|
23 |
Yaprak, H., Karaci, A. and Demir, I. (2013), "Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks", Neur. Comput. Appl., 22, 133-141.
|
24 |
Yilmaz, A. and Degirmenci, N. (2009), "Possibility of using waste tire rubber and fly ash with Portland cement as construction materials", Waste Manage., 29, 1541-1546.
DOI
|
25 |
Yung, W.H., Yung, L.C. and Hua, L.H. (2013), "A study of the durability properties of waste tire rubber applied to self-compacting concrete", Constr. Build. Mater., 41, 665-672.
DOI
|
26 |
Atiş, C.D. and Bilim, C. (2007), "Wet and dry cured compressive strength of concrete containing ground granulated blast-furnace slag", Build. Envir., 42(8), 3060-3065.
DOI
|
27 |
Zhu, J., Zhong, Q., Chen, G. and Li, D. (2012), "Effect of particlesize of blast furnace slag on properties of portland cement", Procedia Eng., 27, 231-236.
|
28 |
Aali, K.A., Parsinejad, M. and Rahmani, B. (2009), "Estimation of saturation percentage of soil using multiple regression, ANN, and ANFIS techniques", Comput. Inform. Sci., 2(3), 127-136.
|
29 |
Adhikary, B.B. and Mutsuyoshi, H. (2006), "Prediction of shear strength of steel fiber RC beams using neural networks", Constr. Build. Mater., 20(9), 801-811.
DOI
|
30 |
Al-Akhras, N.M. and Smadi, M.M. (2004), "Properties of tire rubber ash mortar", Cement Concrete Compos., 26, 821-826.
DOI
|
31 |
Behnood, A., Verian, K.P. and Gharehveran, M.M. (2015), "Evaluation of the splitting tensile strength in plain and steel fiber-reinforced concrete based on the compressive strength", Constr. Build. Mater., 98, 519-529.
DOI
|
32 |
Beycioglu, A., Emiroglu, M., Kocak, Y. and Subasi, S. (2015), "Analyzing the compressive strength of clinker mortars using approximate reasoning approaches-ANN vs MLR", Comput. Concrete, 15(1), 89-101.
DOI
|
33 |
Crossin, E. (2015), "The greenhouse gas implications of using ground granulated blast furnace slag as a cement substitute", J.Clean. Product., 95, 101-108.
DOI
|
34 |
Deb, P.S., Nath, P. and Sarker, P.K. (2014), "The effects of ground granulated blast-furnace slag blending with fly ash and activator content on the workability and strength properties of geopolymer concrete cured at ambient temperature", Mater. Des., 62, 32-39.
DOI
|