[1] De Brito, J., & Saikia, N. (2012).
Recycled aggregate in concrete: use of industrial, construction and demolition waste. Springer Science & Business Media.
https://doi.org/10.1007/978-1-4471-4540-0
[2] Debieb, F., Courard, L., Kenai, S., & Degeimbre, R. (2009). Roller compacted concrete with contaminated recycled aggregates.
Construction and Building Materials,
23(11), 3382-3387.
https://doi.org/10.1016/j.conbuildmat.2009.06.031
[3] Dilbas, H., Çakır, Ö., & Atiş, C. D. (2019). Experimental investigation on properties of recycled aggregate concrete with optimized Ball Milling Method.
Construction and Building Materials,
212, 716-726.
https://doi.org/10.1016/j.conbuildmat.2019.04.007
[4] Dimitriou, G., Savva, P., & Petrou, M. F. (2018). Enhancing mechanical and durability properties of recycled aggregate concrete.
Construction and Building Materials,
158, 228-235.
https://doi.org/10.1016/j.conbuildmat.2017.09.137
[5] Moghimi, M., Shafigh, P., Berengian, J., & Nemati, K. (2010). Experimental Investigation of Effects of Microsilica and Superplasticizer on Some Mechanical Properties of Recycled Concrete Made of Crushed Concrete.
Civil Engineering (Faculty of Engineering),
21(2), 153-162.
https://www.sid.ir/fa/journal/ViewPaper. aspx?id=134394
[6] Choi, W.-C., & Yun, H.-D. (2012). Compressive behavior of reinforced concrete columns with recycled aggregate under uniaxial loading.
Engineering Structures,
41, 285-293.
https://doi.org/10.1016/j.engstruct.2012.03.037
[7] Aghili, L. M., & Ramezanianpour, A. M. (2018). Investigation on the correlations between different physical and mechanical properties of concrete made with recycled concrete aggregate.
MODARES CIVIL ENGINEERING JOURNAL,
18(3), 153-167.
https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=710135
[8] Salimbahrami, S. R., Shakeri, R., & Habibi Hajikolae, B. (2021). Proposed Mix Design of Recycled Concrete Used in Urban Concrete Tables Using Neural Network.
Karafan Quarterly Scientific Journal,
17(4), 209-230.
https://doi.org/10.48301/ kssa.2021.128404
[9] Wagih, A. M., El-Karmoty, H. Z., Ebid, M., & Okba, S. H. (2013). Recycled construction and demolition concrete waste as aggregate for structural concrete.
HBRC Journal,
9(3), 193-200.
https://doi.org/10.1016/j.hbrcj.2013.08.007
[10] Rao, A., Jha, K. N., & Misra, S. (2007). Use of aggregates from recycled construction and demolition waste in concrete.
Resources, Conservation and Recycling,
50(1), 71-81.
https://doi.org/10.1016/j.resconrec.2006.05.010
[11] Chopra, P., Sharma, R. K., & Kumar, M. (2015). Artificial Neural Networks for the Prediction of Compressive Strength of Concrete.
International Journal of Applied Science and Engineering,
13(3), 187-204.
https://doi.org/10.6703/IJASE.2015.13(3).187
[12] Naderpour, H., Rafiean, A. H., & Fakharian, P. (2018). Compressive strength prediction of environmentally friendly concrete using artificial neural networks.
Journal of Building Engineering,
16, 213-219.
https://doi.org/10.1016/j.jobe.2018.01.007
[13] Duan, Z. H., Kou, S. C., & Poon, C. S. (2013). Prediction of compressive strength of recycled aggregate concrete using artificial neural networks.
Construction and Building Materials,
40, 1200-1206.
https://doi.org/10.1016/j.conbuildmat.2012.04.063
[14] Deng, F., He, Y., Zhou, S., Yu, Y., Cheng, H., & Wu, X. (2018). Compressive strength prediction of recycled concrete based on deep learning.
Construction and Building Materials,
175, 562-569.
https://doi.org/10.1016/j.conbuildmat.2018.04.169
[15] Liang, C., Qian, C., Chen, H., & Kang, W. (2018). Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks.
Advances in Materials Science and Engineering,
2018, 1-11.
https://doi.org/10.1155/2018/6204942
[16] Naderpour, H., Noormohammadi, E., & Fakharian, P. (2017). Prediction of punching shear capacity of RC slabs using support vector machine.
Concrete Research,
10(2), 95-107.
https://doi.org/10.22124/JCR.2017.2417
[17] Ling, H., Qian, C., Kang, W., Liang, C., & Chen, H. (2019). Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment.
Construction and Building Materials,
206(3), 355-363.
https://doi.org/10.1016/j.conbuildmat.2019.02.071
[18] Jalal, M., Grasley, Z., Gurganus, C., & Bullard, J. W. (2020). RETRACTED: Experimental investigation and comparative machine-learning prediction of strength behavior of optimized recycled rubber concrete.
Construction and Building Materials,
256(4), 119478.
https://doi.org/10.1016/j.conbuildmat.2020.119478
[19] Ghanizadeh, A. R., Abbaslou, H., Amlashi, A. T., & Alidoust, P. (2019). Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector machine.
Frontiers of Structural and Civil Engineering,
13(1), 215-239.
https://doi.org/10.1007/s11709-018-0489-z
[20] Aiyer, B. G., Kim, D., Karingattikkal, N., Samui, P., & Rao, P. R. (2014). Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine.
KSCE Journal of Civil Engineering,
18(6), 1753-1758.
https://doi.org/10.1007/s12205-014-0524-0
[21] Akande, K. O., Owolabi, T. O., Twaha, S., & Olatunji, S. O. (2014). Performance comparison of SVM and ANN in predicting compressive strength of concrete.
IOSR Journal of Computer Engineering,
16(5), 88-94.
https://doi.org/10.9790/0661-16518894
[22] Gupta, S. (2007). Support vector machines based modelling of concrete strength.
World Academy of Science, Engineering and Technology,
36(1), 305-311.
http://citeseerx. ist.psu.edu/viewdoc/download?doi=10.1.1.360.1088&rep=rep1&type=pdf
[23] Yan, K., Xu, H., Shen, G., & Liu, P. (2013). Prediction of Splitting Tensile Strength from Cylinder Compressive Strength of Concrete by Support Vector Machine.
Advances in Materials Science and Engineering,
2013(2), 1-13.
https://doi.org/10. 1155/2013/597257
[24] Yazdi, J. S., Kalantary, F., & Yazdi, H. S. (2013). Prediction of Elastic Modulus of Concrete Using Support Vector Committee Method.
Journal of Materials in Civil Engineering,
25(1), 9-20.
https://doi.org/10.1061/(ASCE)MT.1943-5533.0000507
[25] Cortes, C., & Vapnik, V. (1995). Support-vector networks.
Machine Learning,
20(3), 273-297.
https://doi.org/10.1007/BF00994018
[26] Dibike, Y. B., Velickov, S., Solomatine, D., & Abbott, M. B. (2001). Model Induction with Support Vector Machines: Introduction and Applications.
Journal of Computing in Civil Engineering,
15(3), 208-216.
https://doi.org/10.1061/(ASCE) 0887-3801(2001)15:3(208)
[27] Samui, P. (2008). Support vector machine applied to settlement of shallow foundations on cohesionless soils.
Computers and Geotechnics,
35(3), 419-427.
https://doi.org/ 10.1016/j.compgeo.2007.06.014
[28] Ferreira, L., Brito, J. d., & Barra, M. (2011). Influence of the pre-saturation of recycled coarse concrete aggregates on concrete properties.
Magazine of Concrete Research,
63(8), 617-627.
https://doi.org/10.1680/macr.2011.63.8.617
[29] Yang, K.-H., Chung, H.-S., & Ashour, A. F. (2008). Influence of Type and Replacement Level of Recycled Aggregates on Concrete Properties.
American Concrete Institute Materials Journal,
105(3), 289-296.
https://bradscholars.brad.ac.uk/handle/10454/7768
[30] Etxeberria, M., Vázquez, E., Marí, A., & Barra, M. (2007). Influence of amount of recycled coarse aggregates and production process on properties of recycled aggregate concrete.
Cement and Concrete Research,
37(5), 735-742.
https://doi.org/ 10.1016/j.cemconres.2007.02.002
[31] Evangelista, L., & de Brito, J. (2007). Mechanical behaviour of concrete made with fine recycled concrete aggregates.
Cement and Concrete Composites,
29(5), 397-401.
https://doi.org/10.1016/j.cemconcomp.2006.12.004
[32] Corinaldesi, V. (2010). Mechanical and elastic behaviour of concretes made of recycled-concrete coarse aggregates.
Construction and Building Materials,
24(9), 1616-1620.
https://doi.org/10.1016/j.conbuildmat.2010.02.031
[33] Fonseca, N., de Brito, J., & Evangelista, L. (2011). The influence of curing conditions on the mechanical performance of concrete made with recycled concrete waste.
Cement and Concrete Composites,
33(6), 637-643.
https://doi.org/10.1016/j. cemconcomp.2011.04.002
[34] Kou, S.-C., & Poon, C.-S. (2008). Mechanical properties of 5-year-old concrete prepared with recycled aggregates obtained from three different sources.
Magazine of Concrete Research,
60(1), 57-64.
https://doi.org/10.1680/macr.2007.00052
[35] Poon, C. S., Shui, Z. H., Lam, L., Fok, H., & Kou, S. C. (2004). Influence of moisture states of natural and recycled aggregates on the slump and compressive strength of concrete.
Cement and Concrete Research,
34(1), 31-36.
https://doi.org/10.1016/ S0008-8846(03)00186-8
[36] Gómez-Soberón, J. M. V. (2002). Porosity of recycled concrete with substitution of recycled concrete aggregate: An experimental study.
Cement and Concrete Research,
32(8), 1301-1311.
https://doi.org/10.1016/S0008-8846(02)00795-0
[37] Khatib, J. M. (2005). Properties of concrete incorporating fine recycled aggregate.
Cement and Concrete Research,
35(4), 763-769.
https://doi.org/10.1016/j.cemconres. 2004.06.017
[38] Fan, C.-C., Huang, R., Hwang, H., & Chao, S.-J. (2016). Properties of concrete incorporating fine recycled aggregates from crushed concrete wastes.
Construction and Building Materials,
112, 708-715.
https://doi.org/10.1016/j.conbuildmat.2016. 02.154
[39] Jariwala, V. H., Patel, P. V., & Purohit, S. P. (2013). Strengthening of RC Beams Subjected to Combined Torsion and Bending with GFRP Composites.
Procedia Engineering,
51(4), 282-289.
https://doi.org/10.1016/j.proeng.2013.01.038
[40] Salimbahrami, S. R. (2021). Prediction of compressive strength of concrete with rubber fibers using artificial neural networks.
Karafan Quarterly Scientific Journal,
18(1), 81-98.
https://doi.org/10.48301/kssa.2021.131038
[41] Olson, D. L., & Delen, D. (2008).
Advanced data mining techniques. Springer Science & Business Media.
https://link.springer.com/book/10.1007/978-3-540-76917-0
[42] Smith, M. (1993).
Neural Networks for Statistical Modeling International Thomson Computer Press.
https://www.amazon.com/Neural-Networks-Statistical-Modeling-Murray/dp/1850328420
