Erratum: Shear Strength Prediction in Reinforced Concrete Deep Beams Using Nature-Inspired Metaheuristic Support Vector Regression (Journal of Computing in Civil Engineering (DOI:10.1061/(ASCE)CP.1943-5487.0000466));Shear Strength Prediction in Reinforced Concrete Deep Beams Using Nature-Inspired Metaheuristic Support Vector Regression

Journal of Computing in Civil Engineering

Volumn 30, Issue 1, 2016, Pages

  Chou, Jui Sheng ^a   Ngo, Ngoc Tri ^a   Pham, Anh Duc ^b  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b THE UNIVERSITY OF DANANG   (Viet Nam)

Author keywords

Deep beams; Evolutionary optimization; Firefly algorithm; Nature inspired metaheuristic algorithm; Reinforced concrete; Shear strength; Support vector regression

Indexed keywords

BIOLUMINESCENCE; CHAOTIC SYSTEMS; EVOLUTIONARY ALGORITHMS; FORECASTING; GLOBAL OPTIMIZATION; LEAST SQUARES APPROXIMATIONS; REGRESSION ANALYSIS; SHEAR STRENGTH;

DEEP BEAM; EVOLUTIONARY OPTIMIZATIONS; FIREFLY ALGORITHMS; META HEURISTIC ALGORITHM; SUPPORT VECTOR REGRESSION (SVR);

REINFORCED CONCRETE;

EID: 84952333479     PISSN: 08873801     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)CP.1943-5487.0000485     Document Type: Erratum

References (40)

1. ACI (American Concrete Institute). (2011). " Building code requirement for structural concrete and commentary." ACI-318, Detroit.
2. Amani, J., and, Moeini, R. (2012). " Prediction of shear strength of reinforced concrete beams using adaptive neuro-fuzzy inference system and artificial neural network." Sci. Iranica, 19 (2), 242-248. 10.1016/j.scient.2012.02.009 SITABC
3. Carlos, G. Q. F., Gustavo, P. M., and, James, K. W. (2007). " Strength of struts in deep concrete members designed using strut-and-tie method." ACI Struct. J., 103 (4), 577-586. ASTJEG 0889-3241
4. Cheng, M.-Y., and, Cao, M.-T. (2014). " Evolutionary multivariate adaptive regression splines for estimating shear strength in reinforced-concrete deep beams." Eng. Appl. Artif. Intell., 28, 86-96. EAAIE6 0952-1976
5. Cheng, M., and, Hoang, N. (2014). " Risk score inference for bridge maintenance project using evolutionary fuzzy least squares support vector machine." J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000275, 04014003. JCCEE5 0887-3801
6. Chou, J.-S., Cheng, M.-Y., and, Wu, Y.-W. (2013). " Improving classification accuracy of project dispute resolution using hybrid artificial intelligence and support vector machine models." Expert Syst. Appl., 40 (6), 2263-2274. 10.1016/j.eswa.2012.10.036 ESAPEH 0957-4174
7. Chou, J.-S., and, Lin, C. (2013). " Predicting disputes in public-private partnership projects: Classification and ensemble models." J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000197, 51-60. JCCEE5 0887-3801
8. Chou, J.-S., and, Pham, A.-D. (2013). " Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength." Constr. Build. Mater., 49, 554-563. CBUMEZ 10.1016/j.conbuildmat.2013.08.078
9. Clark, A. P. (1951). " Diagonal tension in reinforced concrete beams." ACI Struct. J., 48 (10), 145-156.
10. Coelho, L. D. S., and, Mariani, V. C. (2013). " Improved firefly algorithm approach applied to chiller loading for energy conservation." Energy Build., 59, 273-278. 10.1016/j.enbuild.2012.11.030 ENEBDR 0378-7788
11. Duan, K., Keerthi, S. S., and, Poo, A. N. (2003). " Evaluation of simple performance measures for tuning SVM hyperparameters." Neurocomputing, 51, 41-59. 10.1016/S0925-2312(02)00601-X NRCGEO 0925-2312
12. Gandomi, A. H., Alavi, A. H., Shadmehri, D. M., and, Sahab, M. G. (2013). " An empirical model for shear capacity of RC deep beams using genetic-simulated annealing." Arch. Civ. Mech. Eng., 13 (3), 354-369. 10.1016/j.acme.2013.02.007
13. Geisel, T., Nierwetberg, J., and, Zacherl, A. (1985). " Accelerated diffusion in Josephson junctions and related chaotic systems." Phys. Rev. Lett., 54 (7), 616-619. 10.1103/PhysRevLett.54.616 PRLTAO 0031-9007
14. Gerardo, A., Adolfo, B. M., and, Gustavo, J. P.-M. (2002). " Experimental evaluation of design procedures for shear strength of deep reinforced concrete beams." ACI Struct. J., 99 (4), 539-548. ASTJEG 0889-3241
15. He, D., He, C., Jiang, L. G., Zhu, H. W., and, Hu, G. R. (2001). " Chaotic characteristics of a one-dimensional iterative map with infinite collapses." IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 48 (7), 900-906. 10.1109/81.933333
16. Hong, W.-C., Dong, Y., Chen, L.-Y., and, Wei, S.-Y. (2011). " SVR with hybrid chaotic genetic algorithms for tourism demand forecasting." Appl. Soft Comput., 11 (2), 1881-1890. 10.1016/j.asoc.2010.06.003 1568-4946
17. Kavousi-Fard, A., Samet, H., and, Marzbani, F. (2014). " A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting." Expert Syst. Appl., 41 (13), 6047-6056.
18. Kohavi, R. (1995). " A study of cross-validation and bootstrap for accuracy estimation and model selection." Proc., 14th Int. Joint Conf. on Artificial Intelligence, Vol. 2, Morgan Kaufmann Publishers, Montreal, QC, Canada, 1137-1143.
19. Kong, F. K., Robins, P. J., and, Cole, D. F. (1970). " Web reinforcement effects on deep beams." ACI Struct. J., 67 (12), 1010-1017.
20. Kris, D. B. (2011). " Least squares support vector regression with applications to large-scale data: A statistical approach." Ph.D. thesis, Faculty of Engineering, KU Leuven, Katholieke Universiteit Leuven, Belgium.
21. Li, C., and, Li, J. (2012). " Support vector machines approach to conditional simulation of non-Gaussian stochastic process." J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000113, 131-140. JCCEE5 0887-3801
22. Li, Y., Deng, S., and, Xiao, D. (2011). " A novel hash algorithm construction based on chaotic neural network." Neural Comput. Appl., 20 (1), 133-141. 10.1007/s00521-010-0432-2 0941-0643
23. Mansour, M. Y., Dicleli, M., Lee, J. Y., and, Zhang, J. (2004). " Predicting the shear strength of reinforced concrete beams using artificial neural networks." Eng. Struct., 26 (6), 781-799. 10.1016/j.engstruct.2004.01.011 ENSTDF 0141-0296
24. Martins, F. F., Begonha, A., and, Amália Sequeira Braga, M. (2012). " Prediction of the mechanical behavior of the Oporto granite using data mining techniques." Expert Syst. Appl., 39 (10), 8778-8783. 10.1016/j.eswa.2012.02.003 ESAPEH 0957-4174
25. Neal, S. A., and, Julio, A. R. (1989). " Detailing of stirrup reinforcement." ACI Struct. J., 86 (5), 507-515. ASTJEG 0889-3241
26. Oh, J.-K., and, Shin, S.-W. (2001). " Shear strength of reinforced high strength concrete deep beams." ACI Struct. J., 98 (2), 164-173. ASTJEG 0889-3241
27. Olamaei, J., Moradi, M., and, Kaboodi, T. (2013). " A new adaptive modified firefly algorithm to solve optimal capacitor placement problem." Proc., 2013 18th Conf. on Electrical Power Distribution Networks (EPDC), IEEE, 1-6.
28. Pal, M., and, Deswal, S. (2011). " Support vector regression based shear strength modelling of deep beams." Comput. Struct., 89 (13-14), 1430-1439. 10.1016/j.compstruc.2011.03.005 CMSTCJ 0045-7949
29. Pal, S. K., Rai, C. S., and, Singh, A. P. (2012). " Comparative study of firefly algorithm and particle swarm optimization for noisy non-linear optimization problems." Int. J. Intell. Syst. Appl., 4 (10), 50-57.
30. Park, J. W., and, Kuchma, D. (2007). " Strut-and-Tie model analysis for strength prediction of deep beams." ACI Struct. J., 106 (7), 657-666. ASTJEG 0889-3241
31. Smith, K. N., and, Vantsiotis, A. S. (1982). " Shear strength of deep beams." ACI Struct. J., 79 (3), 201-213.
32. Suykens, J. A. K., Gestel, T. V., Brabanter, J. D., Moor, B. D., and, Vandewalle, J. (2002). Least squares support vector machines, World Scientific, Singapore.
33. Tan, K. H., Weng, L. W., and, Teng, S. (1997). " A strut-and-tie model for deep beams subjected to combined top-and-bottom loading." J. Struct. Eng., 75 (13), 215-225.
34. Tan, K.-H., Kong, F.-K., Teng, S., and, Guan, L. (1995). " Web reinforcement effects on deep beams." ACI Struct. J., 92 (37), 395-405. ASTJEG 0889-3241
35. Tan, X.-h., Bi, W.-h., Hou, X.-l., and, Wang, W. (2011). " Reliability analysis using radial basis function networks and support vector machines." Comput. Geotech., 38 (2), 178-186. 10.1016/j.compgeo.2010.11.002 CGEOEU 0266-352X
36. Tang, C., and, Tan, K. (2004). " Interactive mechanical model for shear strength of deep beams." J. Struct. Eng., 10.1061/(ASCE)0733-9445(2004)130:10(1534), 1534-1544.
37. Vapnik, V. N. (1995). The nature of statistical learning theory, Springer, New York.
38. Wang, H., and, Hu, D. (2005). " Comparison of SVM and LS-SVM for regression." Proc., Int. Conf. on Neural Networks and Brain, IEEE, New York, 279-283.
39. Yan, B., Goto, S., Miyamoto, A., and, Zhao, H. (2014). " Imaging-based rating for corrosion states of weathering steel using wavelet transform and PSO-SVM techniques." J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000293, 04014008. JCCEE5 0887-3801
40. Yang, X.-S. (2008). Firefly algorithm, Luniver Press, Bristol, U.K.