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http://dx.doi.org/10.12989/sss.2020.25.2.183

Prediction of concrete strength in presence of furnace slag and fly ash using Hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm)  

Shariati, Mahdi (Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University)
Mafipour, Mohammad Saeed (School of Civil Engineering, College of Engineering, University of Tehran)
Mehrabi, Peyman (Department of Civil Engineering, K.N. Toosi University of Technology)
Ahmadi, Masoud (Department of Civil Engineering, Ayatollah Boroujerdi University)
Wakil, Karzan (Research Center, Sulaimani Polytechnic University)
Trung, Nguyen Thoi (Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University)
Toghroli, Ali (Institute of Research and Development, Duy Tan University)
Publication Information
Smart Structures and Systems / v.25, no.2, 2020 , pp. 183-195 More about this Journal
Abstract
Mineral admixtures have been widely used to produce concrete. Pozzolans have been utilized as partially replacement for Portland cement or blended cement in concrete based on the materials' properties and the concrete's desired effects. Several environmental problems associated with producing cement have led to partial replacement of cement with other pozzolans. Furnace slag and fly ash are two of the pozzolans which can be appropriately used as partial replacements for cement in concrete. However, replacing cement with these materials results in significant changes in the mechanical properties of concrete, more specifically, compressive strength. This paper aims to intelligently predict the compressive strength of concretes incorporating furnace slag and fly ash as partial replacements for cement. For this purpose, a database containing 1030 data sets with nine inputs (concrete mix design and age of concrete) and one output (the compressive strength) was collected. Instead of absolute values of inputs, their proportions were used. A hybrid artificial neural network-genetic algorithm (ANN-GA) was employed as a novel approach to conducting the study. The performance of the ANN-GA model is evaluated by another artificial neural network (ANN), which was developed and tuned via a conventional backpropagation (BP) algorithm. Results showed that not only an ANN-GA model can be developed and appropriately used for the compressive strength prediction of concrete but also it can lead to superior results in comparison with an ANN-BP model.
Keywords
artificial neural network; genetic algorithm; prtial replacement; furnace slag; fly ash;
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Times Cited By KSCI : 60  (Citation Analysis)
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88 Wei, X., Shariati, M., Zandi, Y., Pei, S., Jin, Z., Gharachurlu, S., Abdullahi, M.M., Tahir, M.M. and Khorami, M. (2018), "Distribution of shear force in perforated shear connectors", Steel Compos. Struct., Int. J., 27(3), 389-399. https://doi.org/10.12989/scs.2018.27.3.389
89 Trung, N.T., Shahgoli, A.F., Zandi, Y., Shariati, M., Wakil, K., Safa, M. and Khorami, M. (2019), "Moment-rotation prediction of precast beam-to-column connections using extreme learning machine", Struct. Eng. Mech., Int. J., 70(5), 639-647. https://doi.org/10.12989/sem.2019.70.5.639
90 Vo-Van, T., Nguyen-Thoi, T., Vo-Duy, T., Ho-Huu, V. and Nguyen-Trang, T. (2017), "Modified genetic algorithm-based clustering for probability density functions", J. Statist. Computat. Simul., 87(10), 1964-1979. https://doi.org/10.1080/00949655.2017.1300663   DOI
91 Xie, Q., Sinaei, H., Shariati, M., Khorami, M., Mohamad, E.T. and Bui, D.T. (2019), "An experimental study on the effect of CFRP on behavior of reinforce concrete beam column connections", Steel Compos. Struct., Int. J., 30(5), 433-441. https://doi.org/10.12989/scs.2019.30.5.433
92 Xu, C., Zhang, X., Haido, J.H., Mehrabi, P., Shariati, A., Mohamad, E.T., Hoang, N. and Wakil, K. (2019), "Using genetic algorithms method for the paramount design of reinforced concrete structures", Struct. Eng. Mech., Int. J., 71(5), 503-513. https://doi.org/10.12989/sem.2019.71.5.503
93 Kazerani, S., Fanaie, N. and Soroushnia, S. (2014), "Seismic behavior of drilled beam section in moment connections", J. Numer. Methods Civil Eng., 1(4), 1-6.
94 Katebi, J., Shoaei-parchin, M., Shariati, M., Trung, N.T. and Khorami, M. (2019), "Developed comparative analysis of metaheuristic optimization algorithms for optimal active control of structures", Eng. Comput., 1-20. https://doi.org/10.1007/s00366-019-00780-7
95 Shariati, M., Ramli Sulong, N.H., Suhatril, M., Shariati, A., Arabnejad Khanouki, M.M. and Sinaei, H. (2012c), "Behaviour of C-shaped angle shear connectors under monotonic and fully reversed cyclic loading: An experimental study", Mater. Des., 41, 67-73. https://doi.org/10.1016/j.matdes.2012.04.039   DOI
96 Shariati, M., Ramli Sulong, N., Suhatril, M., Shariati, A., Arabnejad Khanouki, M. and Sinaei, H. (2012d), "Fatigue energy dissipation and failure analysis of channel shear connector embedded in the lightweight aggregate concrete in composite bridge girders", Proceedings of the 5th International Conference on Engineering Failure Analysis, The Hague, The Netherlands, July.
97 Shariati, M., Ramli Sulong, N.H., Suhatril, M., Shariati, A., Arabnejad Khanouki, M.M. and Sinaei, H. (2013), "Comparison of behaviour between channel and angle shear connectors under monotonic and fully reversed cyclic loading", Constr. Build. Mater., 38, 582-593. https://doi.org/10.1016/j.conbuildmat.2012.07.050   DOI
98 Zandi, Y., Shariati, M., Marto, A., Wei, X., Karaca, Z., Dao, D., Toghroli, A., Hashemi, M.H., Sedghi, Y., Wakil, K. and Khorami, M. (2018), "Computational investigation of the comparative analysis of cylindrical barns subjected to earthquake", Steel Compos. Struct., Int. J., 28(4), 439-447. https://doi.org/10.12989/scs.2018.28.4.439
99 Ziaei-Nia, A., Shariati, M. and Salehabadi, E. (2018), "Dynamic mix design optimization of high-performance concrete", Steel Compos. Struct., Int. J., 29(1), 67-75. https://doi.org/10.12989/scs.2018.29.1.067
100 Kaya, M. (2011), "The effects of a new selection operator on the performance of a genetic algorithm", Appl. Mathe. Computat., 217(19), 7669-7678. https://doi.org/10.1016/j.amc.2011.02.070   DOI
101 Khanouki, M.A., Sulong, N.R., Shariati, M. and Tahir, M.M. (2016), "Investigation of through beam connection to concrete filled circular steel tube (CFCST) column", J. Constr. Steel Res., 121, 144-162. https://doi.org/10.1016/j.jcsr.2016.01.002   DOI
102 Khorami, M., Khorami, M., Motahar, H., Alvansazyazdi, M., Shariati, M., Jalali, A. and Tahir, M.M. (2017a), "Evaluation of the seismic performance of special moment frames using incremental nonlinear dynamic analysis".
103 Khorami, M., Alvansazyazdi, M., Shariati, M., Zandi, Y., Jalali, A. and Tahir, M. (2017b), "Seismic performance evaluation of buckling restrained braced frames (BRBF) using incremental nonlinear dynamic analysis method (IDA)", Earthq. Struct., Int. J., 13(6), 531-538. http://dx.doi.org/10.12989/eas.2017.13.6.531
104 Khorramian, K., Maleki, S., Shariati, M. and Sulong, N.R. (2015), "Behavior of tilted angle shear connectors", PLoS One, 10(12), e0144288. https://doi.org/10.1371/journal.pone.0144288   DOI
105 Khorramian, K., Maleki, S., Shariati, M., Jalali, A. and Tahir, M.M. (2017), "Numerical analysis of tilted angle shear connectors in steel-concrete composite systems", Steel Compos. Struct., Int. J., 23(1), 67-85. https://doi.org/10.12989/scs.2017.23.1.067   DOI
106 Le-Duc, T., Ho-Huu, V., Nguyen-Thoi, T. and Nguyen-Quoc, H. (2016), "A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes", Smart Mater. Struct., 25(12), 125020. https://doi.org/10.1088/0964-1726/25/12/125020   DOI
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108 Shariati, M., Shariati, A., Sulong, N.R., Suhatril, M. and Khanouki, M.A. (2014b), "Fatigue energy dissipation and failure analysis of angle shear connectors embedded in high strength concrete", Eng. Fail. Anal., 41, 124-134. https://doi.org/10.1016/j.engfailanal.2014.02.017   DOI
109 Shariati, M., Sulong, N.R., Shariati, A. and Khanouki, M.A. (2015), "Behavior of V-shaped angle shear connectors: experimental and parametric study", Mater. Struct., 49(9), 3909-3926. https://doi.org/10.1617/s11527-015-0762-8
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112 Shariati, M., Sulong, N.R., Shariati, A. and Kueh, A.B.H. (2016), "Comparative performance of channel and angle shear connectors in high strength concrete composites: An experimental study", Constr. Build. Mater., 120, 382-392. https://doi.org/10.1016/j.conbuildmat.2016.05.102   DOI
113 Shariati, M., Toghroli, A., Jalali, A. and Ibrahim, Z. (2017), "Assessment of stiffened angle shear connector under monotonic and fully reversed cyclic loading", Proceedings of the 5th International Conference on Advances in Civil, Structural and Mechanical Engineering - CSM 2017, Zurich, Switzerland.
114 Shariati, M., Trung, N.T., Wakil, K., Mehrabi, P., Safa, M. and Khorami, M. (2019a), "Moment-rotation estimation of steel rack connection using extreme learning machine", Steel Compos. Struct., Int. J., 31(5), 427-435. https://doi.org/10.12989/scs.2019.31.5.427
115 Li, D., Toghroli, A., Shariati, M., Sajedi, F., Bui, D.T., Kianmehr, P., Mohamad, E.T. and Khorami, M. (2019), "Application of polymer, silica-fume and crushed rubber in the production of Pervious concrete", Smart Struct. Syst., Int. J., 23(2), 207-214. https://doi.org/10.12989/sss.2019.23.2.207
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121 Luo, Z., Sinaei, H., Ibrahim, Z., Shariati, M., Jumaat, Z., Wakil, K., Pham, B.T., Mohamad, E.T. and Khorami, M. (2019), "Computational and experimental analysis of beam to column joints reinforced with CFRP plates", Steel nd Compos. Struct., Int. J., 30(3), 271-280. https://doi.org/10.12989/scs.2019.30.3.271
122 Mansouri, I., Safa, M., Ibrahim, Z., Kisi, O., Tahir, M.M., Baharom, S. and Azimi, M. (2016), "Strength prediction of rotary brace damper using MLR and MARS", Struct. Eng. Mech., Int. J., 60(3), 471-488. https://doi.org/10.12989/sem.2016.60.3.471   DOI
123 Shariati, M., Mafipour, M.S., Mehrabi, P., Bahadori, A., Zandi, Y., Salih, M.N.A., Nguyen, H., Dou, J., Song, X. and Poi-Ngian, S. (2019c), "Application of a hybrid artificial neural networkparticle swarm optimization (ANN-PSO) model in behavior prediction of channel shear connectors embedded in normal and high-strength concrete", Appl. Sci., 9(24), 5534. https://doi.org/10.3390/app9245534   DOI