References
1. Whittaker, A., Hamburger, R., and Mahoney, M.
Performance-based engineering of buildings and infrastructure
for extreme loadings", in Proceedings,
AISC-SINY Symposium on Resisting Blast and Progressive
Collapse, American Institute of Steel Construction,
New York (2003).
2. Khurana, A. Report on earthquake of 8th October in
some parts of northern India", EERI (Earthquake Engineering
Research Institute), Special Reports (2005).
3. Liel, A.B., Haselton, C.B., Deierlein, G.G., and Baker,
J.W. Incorporating modeling uncertainties in the
assessment of seismic collapse risk of buildings", Structural
Safety, 31, pp. 197-211 (2009).
4. Ibarra L.F. and Krawinkler, H., Global Collapse of
Frame Structures Under Seismic Excitations, Paci c
Earthquake Engineering Research Center (2005).
5. Benjamin, J.R. and Cornell, C.A., Probability, Statistics,
and Decision for Civil Engineers, Courier Corporation
(2014).
6. Zareian, F., Krawinkler, H., Ibarra, L., and Lignos, D.
Basic concepts and performance measures in prediction
of collapse of buildings under earthquake ground
motions", The Structural Design of Tall and Special
Buildings, 19, pp. 167-181 (2010).
7. Khojastehfar, E., Beheshti-Aval, S.B., Zolfaghari,
M.R., and Nasrollahzade, K. Collapse fragility curve
development using Monte Carlo simulation and arti-
cial neural network", Proceedings of the Institution
of Mechanical Engineers, Part O: Journal of Risk and
Reliability, 228, pp. 301-312 (2014).
8. Beheshti-Aval, S.B., Khojastehfar, E., Noori, M., and
Zolfaghar, M.R. A comprehensive collapse fragility
assessment of moment resisting steel frames considering
various sources of uncertainties", Canadian Journal
of Civil Engineering, 43(2), pp. 118-131 (2016).
9. Lagaros N.D. and Fragiadakis, M. Fragility assessment
of steel frames using neural networks", Earthquake
Spectra, 23, pp. 735-752 (2007).
2952 F. Karimi Ghaleh Jough and S.B. Beheshti Aval/Scientia Iranica, Transactions A: Civil Engineering 25 (2018) 2938{2953
10. Mitropoulou, C.C. and Papadrakakis, M. Developing
fragility curves based on neural network IDA predictions",
Engineering Structures, 33, pp. 3409-3421
(2011).
11. Cardaliaguet, P. and Euvrard, G. Approximation of
a function and its derivative with a neural network",
Neural Networks, 5, pp. 207-220 (1992).
12. Li, X. Simultaneous approximations of multivariate
functions and their derivatives by neural networks with
one hidden layer", Neurocomputing, 12, pp. 327-343
(1996).
13. Chapman, O. and Crossland, A. Neural networks
in probabilistic structural mechanics", in Probabilistic
Structural Mechanics Handbook, pp. 317-330 (1995).
14. Atmaca, H., Cetisli, B., and Yavuz, H.S., The Comparison
of Fuzzy Inference Systems and Neural Network
Approaches with ANFIS Method for Fuel Consumption
Data, Yavuz Osmangazi University, Electrical and
Electronic Engineering Department (2001).
15. Farahani, M.K. and Mehralian, S. Comparison between
arti cial neural network and neuro-fuzzy for gold
price prediction", Fuzzy Systems (IFSC), 13th Iranian
Conference on, At Qazvin, Iran (2013).
16. Vamvatsikos, D. and Cornell, C.A. Incremental dynamic
analysis", Earthquake Engineering & Structural
Dynamics, 31, pp. 491-514 (2002).
17. Zareian, F., Lignos, D.G. and Krawinkler, H. Quanti
cation of modeling uncertainties for collapse assessment
of structural systems under seismic excitations",
in Proceedings of the 2nd International Conference on
Computational Methods in Structural Dynamics and
Earthquake Engineering (COMPDYN 2009), pp. 22-
24 (2009).
18. Beheshti-Aval, S.B., Verki, A.M., and Rastegaran,
M. Systematical approach to evaluate probability of
steel MRF buildings based on engineering demand and
intensity measure", Proc. of the Intl. Conf. on Advances
in Civil, Structural and Mechanical Engineering
(2014).
19. Zareian F. and Krawinkler, H. Assessment of probability
of collapse and design for collapse safety",
Earthquake Engineering & Structural Dynamics, 36,
pp. 1901-1914 (2007).
20. Celarec, D. and Dolsek, M. The impact of modelling
uncertainties on the seismic performance assessment
of reinforced concrete frame buildings", Engineering
Structures, 52, pp. 340-354 (2013).
21. Rubinstein, R.Y. and Kroese, D.P., Simulation and the
Monte Carlo Method, 707, John Wiley & Sons (2011).
22. Esteva, L. and Ruiz, S.E. Seismic failure rates of
multistory frames", Journal of Structural Engineering,
115, pp. 268-284 (1989).
23. Baker, J.W. and Cornell, C.A. A vector-valued
ground motion intensity measure consisting of spectral
acceleration and epsilon", Earthquake Engineering &
Structural Dynamics, 34, pp. 1193-1217 (2005).
24. He, J.N. and Wang, Z. Analysis on system reliability
of steel framework structure and optimal design",
Applied Mechanics and Materials, 105, pp. 902-906
(2011).
25. Seo, J. and Linzell, D.G. Horizontally curved steel
bridge seismic vulnerability assessment ", Engineering
Structures, 34, pp. 21-32 (2012).
26. Liel, A.B., Haselton, C.B., Deierlein, G.G., and Baker,
J.W. Incorporating modelling uncertainties in the
assessment of seismic collapse risk of buildings", Structural
Safety, 31(2), pp. 197-211 (2009).
27. Rajeev, P. and Tesfamariam, S. Seismic fragilities
for reinforced concrete buildings with consideration of
irregularities", Structural Safety, 39, pp. 1-13 (2012).
28. Jang, J.S.R. ANFIS: adaptive-network-based fuzzy
inference system", Systems, Man and Cybernetics,
IEEE Transactions on, 23, pp. 665-685 (1993).
29. Bezdek, J.C., Pattern Recognition with Fuzzy Objective
Function Algorithms, Springer Science & Business
Media (2013).
30. Jang, J.S.R., Sun, C.T., and Mizutani, E., Neuro-
Fuzzy and Soft Computing; a Computational Approach
to Learning and Machine Intelligence, Upper Saddle
River, NJ: Prentice-Hall (1997).
31. Chiu, S.L. Fuzzy model identi cation based on cluster
estimation", Journal of Intelligent and Fuzzy Systems,
2, pp. 267-278 (1994).
32. Dunn, J.C. A Fuzzy relative of the ISODATA process
and its use in detecting compact well-separated
clusters", Journal of Cybernetics, 3, pp. 32-57 (1973).
33. UBC Uniform building code", in Int. Conf. Building
Ocials (1997).
34. Ibarra, L.F., Medina, R.A., and Krawinkler, H. Hysteretic
models that incorporate strength and sti ness
deterioration", Earthquake Engineering and Structural
Dynamics, 34, pp. 1489-1512 (2005).
35. Ellingwood, B.R. and Kinali, K. Quantifying and
communicating uncertainty in seismic risk assessment",
Structural Safety, 31, pp. 179-187 (2009).
36. Foutch, D.A. and Yun, S.Y. Modeling of steel moment
frames for seismic loads", Journal of Constructional
Steel Research, 58, pp. 529-564 (2002).
37. Medina R.A. and Krawinkler, H., Seismic Demands
for Nondeteriorating Frame Structures and Their Dependence
on Ground Motions, Paci c Earthquake Engineering
Research Center (2004).
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