Neuro-fuzzy and artificial neural networks modeling of uniform temperature effects of symmetric parabolic haunched beams

- Journal title : Structural Engineering and Mechanics
- Volume 56, Issue 5, 2015, pp.787-796
- Publisher : Techno-Press
- DOI : 10.12989/sem.2015.56.5.787

Title & Authors

Neuro-fuzzy and artificial neural networks modeling of uniform temperature effects of symmetric parabolic haunched beams

Yuksel, S. Bahadir; Yarar, Alpaslan;

Yuksel, S. Bahadir; Yarar, Alpaslan;

Abstract

When the temperature of a structure varies, there is a tendency to produce changes in the shape of the structure. The resulting actions may be of considerable importance in the analysis of the structures having non-prismatic members. The computation of design forces for the non-prismatic beams having symmetrical parabolic haunches (NBSPH) is fairly difficult because of the parabolic change of the cross section. Due to their non-prismatic geometrical configuration, their assessment, particularly the computation of fixed-end horizontal forces and fixed-end moments becomes a complex problem. In this study, the efficiency of the Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) in predicting the design forces and the design moments of the NBSPH due to temperature changes was investigated. Previously obtained finite element analyses results in the literature were used to train and test the ANN and ANFIS models. The performances of the different models were evaluated by comparing the corresponding values of mean squared errors (MSE) and decisive coefficients (). In addition to this, the comparison of ANN and ANFIS with traditional methods was made by setting up Linear-regression (LR) model.

Keywords

non-prismatic member;finite element analysis;parabolic haunch;artificial neural networks, adaptive neuro fuzzy inference systems;

Language

English

Cited by

References

1.

Arslan, M.E. and Durmus, A. (2014), "Fuzzy logic approach for estimating bond behavior of lightweight concrete", Comput. Concrete, 14(3), 233-245.

2.

Bathe, K.J. (1996), Finite Element Procedures, Prentice Hall Publisher, NJ, USA.

3.

Bedirhanoglu, I. (2014), "A practical neuro-fuzzy model for estimating modulus of elasticity of concrete", Struct. Eng. Mech., 51(2), 249-265.

4.

Dorum, A., Yarar, A., Sevimli M.F. and Onucyildiz, M. (2010), "Modelling the rainfall-runoff data of susurluk basin", Exp. Syst. Appl., 37(9), 6587-6593.

5.

Drake, J.T. (2000), "Communications phase synchronization using the adaptive network fuzzy inference system", Ph.D. Thesis, New Mexico State University, Las Cruces, New Mexico, USA.

6.

El-Mezaini, N., Balkaya, C. and Citipioglu, E. (1991), "Analysis of frames with nonprismatic members", J. Struct. Eng., ASCE, 117(6), 1573-1592.

7.

Hakim, S.J.S. and Abdul Razak, H. (2013), "Adaptive Neuro fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification", Struct. Eng. Mech., 45(6), 779-802.

8.

Ham, F.M., Kostanic, I. (2001), Principles of Neurocomputing for Science and Engineering, McGraw Hill, New York, NY, USA.

9.

Jang, J.S.R. (1993), "ANFIS: adaptive-network-based fuzzy inference system", IEEE Tran. Syst. Manag. Cyber, 23(3), 665-685.

10.

Jang, J.S.R., Sun, C.T. and Mizutani, E. (1997), Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice-Hall, Upper Saddle River.

11.

Kisi, O. (2006), "Daily pan evaporation modelling using a neuro-fuzzy computing technique", J. Hydrol., 329, 636-646.

12.

Kose, M.M. and Kayadelen, C. (2013), "Effects of infill walls on RC buildings under time history loading using genetic programming and neuro-fuzzy", Struct. Eng. Mech., 47(3), 401-419.

13.

Markandeya, R.P., Rajsekhar, K. and Sandeep, R.T. (2014), "Performance of non-prismatic simply supported prestressed concrete beams", Struct. Eng. Mech., 52(4), 723-738.

14.

Mohammadhassani, M., Nezamabadi-Pour, H., Jumaat, M., Jameel., M., Hakim, S.J.S. and Zargar, M. (2013), "Application of the ANFIS model in deflection prediction of concrete deep beam", Struct. Eng. Mech., 45(3), 319-332.

15.

Mohammadhassani, M., Nezamabadi-Pour, H., Suhatril, M. and Sariati, M. (2014), "An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups", Smart Struct. Syst., 15(4), 785-809.

16.

Moller, M.B. (1993), "A scaled conjugate gradient algorithm for fast supervised learning", Neural Networks, 525-533.

17.

Saffari, H., Mohammadnejad, M. and Bagheripour, M.H. (2012), "Free vibration analysis of non-prismatic beams under variable axial forces", Struct. Eng. Mech., 43(5), 561-582.

18.

Yarar, A., Onucyildiz, M. and Copty, N.K. (2009), "Modelling Level Change In Lakes Using Neuro-Fuzzy And Artificial Neural Networks", J. Hydrol., 365(3), 329-334.

19.

Yuksel, S.B. (2009), "Behavior of symmetrically haunched non-prismatic members subjected to temperature changes", Struct. Eng. Mech., 31(3), 203-207.

20.

Yuksel, S.B. (2011), "Discussion of the paper 'Equivalent representations of beams with periodically variable cross-sections' by Tianxin Zheng and Tianjian Ji", Eng. Struct., 33(10), 2953-2955.

21.

Yuksel, S.B. (2012), "Assessment of non-prismatic beams having symmetrical parabolic haunches with constant haunch length ratio of 0.5", Struct. Eng. Mech., 32(6), 849-866.

22.

Yuksel, S.B. and Yarar, A. (2014a), "Artificial Neural Network (ANN) modelling of the parabolic haunched beams subjected to uniform temperature change", 15th EU/ME Workshop: Metaheuristics and Engineering, Istanbul, Turkey, March.

23.

Yuksel, S.B. and Yarar, A. (2014b), "Modelling uniform temperature effects of symmetric parabolic haunched beams using Adaptive Neuro Fuzzy Inference Systems (ANFIS)", 15th EU/ME Workshop: Metaheuristics and Engineering, Istanbul, Turkey, March.

24.

Yuksel, S.B. and Yarar, A. (2014c), "Modeling uniform temperature effects of symmetric parabolic haunched beams using Neuro-Fuzzy and Artificial Neural Networks", ICESA 2014 International Civil Engineering & Architecture Symposium for Academicians 2014, Side, Antalya, Turkey, May.

25.

Zheng, T. and Ji, T. (2011), "Equivalent representations of beams with periodically variable cross-section", Eng. Struct., 39(14), 1569-1583.