Top

Neural Computing and Applications

Published in:

01-12-2013 | Original Article

Design of wavelet neural networks based on symmetry fuzzy C-means for function approximation

Authors: Zarita Zainuddin, Pauline Ong

Published in: Neural Computing and Applications | Special Issue 1/2013

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Specifying the number and locations of the translation vectors for wavelet neural networks (WNNs) is of paramount significance as the quality of approximation may be drastically reduced if initialization of WNNs parameters was not done judiciously. In this paper, an enhanced fuzzy C-means algorithm, specifically the modified point symmetry–based fuzzy C-means algorithm (MPSDFCM), was proposed, in order to determine the optimal initial locations for the translation vectors. The proposed neural network models were then employed in approximating five different nonlinear continuous functions. Assessment analysis showed that integration of the MPSDFCM in the learning phase of WNNs would lead to a significant improvement in WNNs prediction accuracy. Performance comparison with the approaches reported in the literature in approximating the same benchmark piecewise function verified the superiority of the proposed strategy.

previous article Comparison of multi-objective evolutionary neural network, adaptive neuro-fuzzy inference system and bootstrap-based neural network for flood forecasting

next article Adaptive fuzzy output feedback control of nonlinear uncertain systems with unknown backlash-like hysteresis based on modular design

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Abiyev RH (2011) Fuzzy wavelet neural network based on fuzzy clustering and gradient techniques for time series prediction. Neural Comput Appl 20(2):249–259. doi:10.1007/s00521-010-0414-4 CrossRef

Cao J, Lin X (2008) Application of the diagonal recurrent wavelet neural network to solar irradiation forecast assisted with fuzzy technique. Eng Appl Artif Intel 21(8):1255–1263. doi:10.1016/j.engappai.2008.02.003 MathSciNetCrossRef

Cao JW, Lin ZP, Huang GB (2010) Composite function wavelet neural networks with extreme learning machine. Neurocomputing 73(7–9):1405–1416. doi:10.1016/j.neucom.2009.12.007 CrossRef

Chen CH, Hsu CF (2010) Recurrent wavelet neural backstepping controller design with a smooth compensator. Neural Comput Appl 19(7):1089–1100. doi:10.1007/s00521-010-0347-y CrossRef

Chen JH, Bruns DD (1995) WaveARX neural-network development for system-identification using a systematic design synthesis. Ind Eng Chem Res 34(12):4420–4435CrossRef

Chung KL, Lin JS (2007) Faster and more robust point symmetry-based K-means algorithm. Pattern Recogn 40(2):410–422. doi:10.1016/j.patcog.2005.09.015 MathSciNetCrossRefMATH

Friedman M (1940) A comparison of alternative tests of significance for the problem of m rankings. Ann Math Stat 11(1):86–92CrossRef

Gougam LA, Tribeche M, Mekideche-Chafa F (2008) A systematic investigation of a neural network for function approximation. Neural Netw 21(9):1311–1317. doi:10.1016/j.neunet.2008.06.015 CrossRefMATH

Gutierrez JM, Gutes A, Cespedes F, del Valle M, Munoz R (2008) Wavelet neural networks to resolve the overlapping signal in the voltammetric determination of phenolic compounds. Talanta 76(2):373–381. doi:10.1016/j.talanta.2008.03.009 CrossRef

10.

Han M, Yin J (2008) The hidden neurons selection of the wavelet networks using support vector machines and ridge regression. Neurocomputing 72(1–3):471–479. doi:10.1016/j.neucom.2007.12.009 CrossRef

11.

Hargreaves JC, Abe-Ouchi A (2003) Timing of ice-age terminations determined by wavelet methods. Paleoceanography 18(2). doi:10.1029/2002pa000825

12.

Ho DWC, Zhang PA, Xu JH (2001) Fuzzy wavelet networks for function learning. IEEE T Fuzzy Syst 9(1):200–211CrossRef

13.

Hsu CC, Lu TC (2008) Minimum-phase criterion on sampling time for sampled-data interval systems using genetic algorithms. Appl Soft Comput 8(4):1670–1679. doi:10.1016/j.asoc.2008.01.009 CrossRef

14.

Hwang K, Mandayam S, Udpa SS, Udpa L, Lord W, Atzal M (2000) Characterization of gas pipeline inspection signals using wavelet basis function neural networks. NDT E Int 33(8):531–545CrossRef

15.

Karatepe E, Alci M (2005) A new approach to fuzzy wavelet system modeling. Int J Approx Reason 40(3):302–322. doi:10.1016/j.ijar.2005.06.003 MathSciNetCrossRef

16.

Lin C-J (2006) Wavelet neural networks with a hybrid learning approach. J Inf Sci Eng 22:1367–1387

17.

MathWorks (2010) Matlab. The MathWorks Inc, Massachusetts

18.

Ortiz-Garcia EG, Salcedo-Sanz S, Perez-Bellido AM, Portilla-Figueras JA (2009) Improving the training time of support vector regression algorithms through novel hyper-parameters search space reductions. Neurocomputing 72(16–18):3683–3691. doi:10.1016/j.neucom.2009.07.009 CrossRef

19.

Oussar Y, Dreyfus G (2000) Initialization by selection for wavelet network training. Neurocomputing 34:131–143CrossRefMATH

20.

Ramuhalli P, Udpa L, Udpa SS (2002) Electromagnetic NDE signal inversion by function-approximation neural networks. IEEE T Magn 38(6):3633–3642. doi:10.1109/Tmag.2002.804817 CrossRef

21.

Shamir R, Hartuv E, Schmitt AO, Lange J, Meier-Ewert S, Lehrach H (2000) An algorithm for clustering cDNA fingerprints. Genomics 66(3):249–256. doi:10.1006/geno.2000.6187 CrossRef

22.

Singh M, Srivastava S, Hanmandlu M, Gupta JRP (2009) Type-2 fuzzy wavelet networks (T2FWN) for system identification using fuzzy differential and Lyapunov stability algorithm. Appl Soft Comput 9(3):977–989. doi:10.1016/j.asoc.2008.03.017 CrossRef

23.

Srivastava S, Singh M, Hanmandlu M, Jha AN (2005) New fuzzy wavelet neural networks for system identification and control. Appl Soft Comput 6(1):1–17. doi:10.1016/j.asoc.2004.10.001 CrossRef

24.

Su MC, Chou CH, Hsieh CC (2005) Fuzzy C-means algorithm with a point symmetry distance. Int J Fuzzy Syst 7:175–181

25.

Su MS, Chou CH (2001) A modified version of the K-means algorithm with a distance based on cluster symmetry. IEEE T Pattern Anal 23(6):674–680CrossRef

26.

Tzeng ST (2010) Design of fuzzy wavelet neural networks using the GA approach for function approximation and system identification. Fuzzy Set Syst 161(19):2585–2596. doi:10.1016/j.fss.2010.06.002 MathSciNetCrossRef

27.

Wang J, Xiao J, Peng H, Gao X (2005) Constructing fuzzy wavelet network modeling. Int J Inform Techno 11(6):68–74

28.

Wei M, Jin S, Wang I (2004) Defect characteristic prediction of pipeline by means of wavelet neural network based on hierarchical clustering algorithm. In: Proceedings of biennial international pipeline conference, pp 921–924

29.

Yao S, Wei CJ, He ZY (1996) Evolving wavelet neural networks for function approximation. Electron Lett 32(4):360–361CrossRef

30.

Zainuddin Z, Ong P (2012) An effective and novel wavelet neural network approach in classifying type 2 diabetics. Neural Netw World 22(5):407–428

31.

Zainuddin Z, Ong P (2011) Modified wavelet neural network in function approximation and its application in prediction of time-series pollution data. Appl Soft Comput 11(8):4866–4874. doi:10.1016/j.asoc.2011.06.013 CrossRef

32.

Zainuddin Z, Ong P (2011) Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network. Expert Syst Appl 38(11):13711–13722. doi:10.1016/j.eswa.2011.04.164

33.

Zainuddin Z, Wan Daud WR, Ong P, Shafie A (2011) Wavelet neural networks applied to pulping of oil palm fronds. Bioresour Technol 102:10978–10986. doi:10.1016/j.biortech.2011.09.080 CrossRef

34.

Zhang QG, Benveniste A (1992) Wavelet networks. IEEE T Neural Netw 3(6):889–898CrossRef

35.

Zhou B, Shi AG, Cai F, Zhang YS (2004) Wavelet neural networks for nonlinear time series analysis. Lect Notes Comput Sci 3174:430–435CrossRef

Title: Design of wavelet neural networks based on symmetry fuzzy C-means for function approximation
Authors: Zarita Zainuddin
Pauline Ong
Publication date: 01-12-2013
Publisher: Springer London
Published in: Neural Computing and Applications / Issue Special Issue 1/2013
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-013-1350-x

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Other articles of this Special Issue 1/2013

Fuzzy genetic approach for modeling of the critical submergence of an intake

Assessment of the effect on technical efficiency of bad loans in banking industry: a principal component analysis and neuro-fuzzy system

Developing a new model based on neuro-fuzzy system for predicting roof fall in coal mines

Efficiency appraisal and ranking of decision-making units using data envelopment analysis in fuzzy environment: a case study of Tehran stock exchange

Improvement of customers’ satisfaction with new product design using an adaptive neuro-fuzzy inference systems approach

Multi-sensor fault tolerant measurement based on Tagaki–Sugeno fuzzy model

Premium Partner