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Neural Computing and Applications

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04-03-2017 | Original Article

Functional link neural network approach to solve structural system identification problems

Authors: Deepti Moyi Sahoo, S. Chakraverty

Published in: Neural Computing and Applications | Issue 11/2018

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Abstract

System identification problems are generally inverse vibration problems. Sometimes it is difficult to handle the inverse problems by traditional methods and classical artificial neural network. As such, the objective of this paper is to identify structural parameters by developing a novel functional link neural network (FLNN) model. FLNN model is more efficient than multi-layer neural network (MNN) as computation is less because hidden layer is not required. Here, single-layer neural network with multi-input and multi-output with feed-forward neural network model and principle of error back propagation has been used to identify structural parameters. The hidden layer is excluded by enlarging the input patterns with the help of Legendre and Hermite polynomials. Comparison of results among MNN, Legendre neural network, Hermite neural network and desired is considered and it is found that FLNN models are more effective than MNN.

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Ali HH, Haweel MT (2012) Legendre neural networks with multi input multi output system equations. In: Seventh international conference on computer engineering and systems (ICCES), 2012. Cairo, pp 92–97

Bhat RB, Chakraverty S (2011) Numerical analysis in engineering. Narosa Publication, Navi Mumbai, pp 1–330

Chakraverty S (2009) Vibration of plates. Taylor & Francis, CRC Press, London, Boca Raton, pp 1–411

Chakraverty S, Sahoo DM (2014) Interval response data based system identification of multi storey shear buildings using interval neural network modelling. Comput Assist Methods Eng Sci 21(2):123–140MathSciNet

Chakraverty S, Behera D (2014) Parameter identification of multistorey frame structure from uncertain dynamic data. Strojniški vestnik J Mech Eng 60(5):331–338CrossRef

Chiang HK, Chu CT (2015) Reference model with an adaptive hermite fuzzy neural network controller for tracking a synchronous reluctance motor. Electr Power Compon Syst 43(7):770–780CrossRef

Dinh HM, Nagayama T, Fujino Y (2012) Structural parameter identification by use of additional known masses and its experimental application. Struct Control Health Monit 19:436–450CrossRef

Ebrahimian M, Todorovska MI (2015) Structural system identification of buildings by a wave method based on a nonuniform timoshenko beam model. J Eng Mech 141(8):04015022-1–04015022-11CrossRef

Facchini L, Betti M, Biagini P (2014) Neural network based modal identification of structural systems through output-only measurement. Comput Struct 138:183–194CrossRef

10.

Fan W, Qiao P (2011) Vibration-based damage identification methods: a review and comparative study. Struct Health Monit 10:83–111CrossRef

11.

Gerald CF (2004) Applied numerical analysis. Pearson Education, Upper Saddle River, pp 1–609

12.

Guo Y, Kwon DK, Kareem A (2016) Near-real-time hybrid system identification framework for civil structures with application to Burj Khalifa. J Struct Eng 142(2):04015132-1–04015132-15

13.

Hassim YMM, Ghazali R (2012) Using artificial bee colony to improve functional link neural network training. Appl Mech Mater 263–266:2102–2108CrossRef

14.

Jianping H, Peijuan Z, Hongtao W (2014) Structural modal parameter identification and damage diagnosis based on Hilbert–Huang transform. Earthq Eng Eng Vib 13:101–111CrossRef

15.

Kerschen G, Worden K, Vakakis AF, Golinval JC (2007) Nonlinear system identification in structural dynamics: current status and future directions. In: 25th international modal analysis conference, Orlando, Floride, USA. pp 1–26

16.

Khanmirza E, Khaji N, Majd VJ (2011) Model updating of multistory shear buildings for simultaneous identification of mass, stiffness and damping matrices using two different soft computing methods. Expert Syst Appl 38(5):5320–5329CrossRef

17.

Khanmirza E, Khaji N, Khanmirza E (2014) Identification of linear and non-linear physical parameters of multistorey shear buildings using artificial neural network. Inverse Probl Sci Eng 23(4):670–687CrossRef

18.

Lei Y, Jiang YQ (2011) A two-stage Kalman estimation approach for the identification of nonlinear structural parameters. Proc Eng 14:3088–3094CrossRef

19.

Lei Y, Su Y, Shen W (2013) A probabilistic damage identification approach for structures under unknown excitation and with measurement uncertainties. J Appl Math 2013:1–7CrossRef

20.

Li W, Deng C (2012) Fast and robust method for dynamic gesture recognition using hermite neural network. J Comput 7(5):1163–1168

21.

Ma L, Khorasani K (2005) Constructive feedforward neural networks using Hermite polynomial activation functions. IEEE Trans Neural Netw 16(4):821–833CrossRef

22.

Mackenzie MR, Tieu AK (2003) Hermite neural network correlation and application. IEEE Trans Signal Process 51(12):3210–3219MathSciNetCrossRef

23.

Mackenzie M, Tieu K (2004) Gaussian filters and filter synthesis using a Hermite/Laguerre neural network. IEEE Trans Neural Netw 15(1):206–214CrossRef

24.

Misra BB, Dehuri S (2007) Functional link artificial neural network for classification task in data mining. J Comput Sci 3(12):948–955CrossRef

25.

Mishra SK, Panda G, Meher S, Sahoo AK (2009) Exponential functional link artificial neural networks for denoising of image corrupted by gaussian noise. In: ICACC ‘09 international conference on advanced computer control, Singapore. pp 355–359

26.

Nanda SK, Tripathy DP (2011) Application of Legendre neural network for air quality prediction. In: The 5th PSU-UNS international conference on engineering and technology (ICET-2011), Phuket, Prince of Songkla University, Faculty of Engineering Hat Yai, Songkhla, Thailand, 2–3 May 2011

27.

Nanda SK, Tripathy DP (2011) Application of functional link artificial neural network for prediction of machinery noise in opencast mines. Adv Fuzzy Syst 2011:1–11CrossRef

28.

Pao YH (1989) Adaptive pattern recognition and neural networks. Addison-Weseley Longman Publishing Co., BostonMATH

29.

Panda G, Das DP (2003) Functional link artificial neural network for active control of nonlinear noise processes. In: International workshop on acoustic echo and noise control (IWAENC2003), September, Kyoto, Japan, pp 163–166

30.

Parija S, Sahu PK, Nanda SK (2013) A functional link artificial neural network for location management in cellular network. In: International conference on information communication and embedded systems (ICICES), Chennai, pp 1160–1164

31.

Patra JC, Chin WC, Meher PK, Chakraborty G (2008) Legendre-FLANN-based nonlinear channel equalization in wireless communication system. In: IEEE international conference on systems, man and cybernetics (SMC 2008), pp 1826–1831

32.

Patra JC, Meher PK, Chakraborty G (2009) Nonlinear channel equalization for wireless communication systems using Legendre neural networks. Signal Process 89:2251–2262CrossRef

33.

Patra JC, Bornand C (2010) Nonlinear dynamic system identification using Legendre neural network. In: The 2010 international joint conference on neural networks (IJCNN), Barcelona, pp 1–7

34.

Sahoo DM, Chakraverty S (2013) Fuzzified data based neural network modeling for health assessment of multistorey shear buildings. Adv Artif Neural Syst 2013:1–12CrossRef

35.

Sahoo DM, Das A, Chakraverty S (2014) Interval data-based system identification of multistorey shear buildings by artificial neural network modelling. Archit Sci Rev 58(3):244–254CrossRef

36.

Sirca GF Jr, Adeli H (2012) System Identification in structural engineering. Sci Iran 19(6):1355–1364CrossRef

37.

Wang F, Ling X, Xu X, Zhang F (2014) Structural stiffness identification based on the extended Kalman filter research. Abst Appl Anal 2014:1–8MathSciNet

38.

Yuan XH, Feng QY, Zeng TJ, Ma HB (2013) Digital predistortion for RF power amplifiers based on enhanced orthonormal Hermite polynomial basis neural network. In: Progress in electromagnetics research symposium proceedings, (PIERS), Taipei, 25–28 March, pp 1130–1133

39.

Zhou C, Chase JG, Rodgers GW, Tomlinson H (2015) Physical parameter identification of structural systems with hysteretic pinching. Comput Aided Civil Infrastruct Eng 30:247–262CrossRef

40.

Zurada JM (1994) Introduction to artificial neural systems. Jaico Publishing House, Mumbai, pp 1–759

Title: Functional link neural network approach to solve structural system identification problems
Authors: Deepti Moyi Sahoo
S. Chakraverty
Publication date: 04-03-2017
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 11/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-017-2907-x

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