Treatment of skewed multi-dimensional training data to facilitate the task of engineering neural models

Expert Systems with Applications

Volumn 33, Issue 4, 2007, Pages 978-983

  Altun, H ^a   Bilgil, A ^a   Fidan, B C ^b  

^a NIGDE UNIVERSITY   (Turkey)

^b YILDIZ TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Backpropagation; Multi dimensional data treatment; Multilayered perceptron; Skewness; Suspended sediment prediction

Indexed keywords

BACKPROPAGATION; COMPUTER SIMULATION; NEURAL NETWORKS; PARAMETER ESTIMATION; PROBLEM SOLVING;

MULTI-DIMENSIONAL DATA TREATMENT; MULTILAYERED PERCEPTRON; SKEWNESS; SUSPENDED SEDIMENT PREDICTION;

DATA REDUCTION;

EID: 33947626066     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2006.07.010     Document Type: Article

References (23)

1. Altun, H., Bilgil, A., & Fidan, C. B. (2006). Treatment of multi-dimensional data to enhance neural network estimators in regression problems. Expert Systems with Applications. Available from http://www.sciencedirect.com/.
2. Bullinaria, J. A. (2005). Evolving neural networks: is it really worth the effort? In Proceedings of the European symposium on artificial neural networks, pp. 267-272.
3. Cheng N.S., and Chiew Y.M. Analysis of initiation of sediment suspension from bed load. Journal of Hydraulic Engineering, ASCE 125 (1999) 855-860
4. Cigizoglu H.K. Suspended sediment estimation and forecasting using artificial neural networks. Turkish Journal of Engineering and Environmental Science 26 (2002) 15-25
5. Cigizoglu H.K., and Alp M. Generalized regression neural network in modeling river sediment yield. Advances in Engineering Software 37 (2006) 63-68
6. EIE (2002). Sediment data and sediment transport amount for surface water in Turkey. Elektrik Işleri Etüt Idaresi (in Turkish).
7. Einstein, H. A. (1950). The bed load function for sediment transportation in open channel flows. Technical Bulletin 1026, US Department of Agriculture, Washington, DC.
8. Esposito, A., Aversano, G., & Quek, F. (2001). Optimal parameters in neural network models. In The 12th Italian workshop on neural nets, May 17-19.
9. García-Pedrajas, N., Ortiz-Boyer, D., & Hervás-Martínez, C. (2005). An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization. Neural Networks. Available online 15 December 2005 from http://www.sciencedirect.com/.
10. Ghedira, H., & Bernier, M. (2004). The effect of some internal neural network parameters on SAR texture classification performance. In IEEE geoscience and remote sensing symposium, vol. 6, pp. 3845-3848.
11. Krimpenis, A., & Vosniakos, G. C. (2005). Initialisation improvement in engineering feedforward ANN models. In European symposium on artificial neural networks, 27-29 April.
12. Ma L., and Khorasani K. A new strategy for adaptively constructing multilayer feedforward neural networks. Neurocomputing 51 (2003) 361-385
13. Misri R.L., Ranga Raju K.G., and Garde R.J. Bed load transport of course nonuniform sediments. Journal of Hydraulic Engineering 110 (1984) 312-328
14. Nagy H.M., Watanabe K., and Hirano M. Prediction of sediment load concentration in rivers using artificial neural network model. Journal of Hydraulic Engineering 128 (2002) 588-595
15. Patel P.L., and Ranga Raju K.G. Fraction wise calculation of bed load transport. Journal of Hydraulic Research 34 3 (1996)
16. Samaga B.R., Ranga Raju K.G., and Garde R.J. Suspended load transport rate of sediment mixture. Journal of Hydraulic Engineering 112 (1986) 1019-1038
17. Saxén, H., & Pettersson, F. (2006). Method for the selection of inputs and structure of feedforward neural networks. Computers & Chemical Engineering. Available online 20 March 2006 from http://www.sciencedirect.com/.
18. Şentürk F. Bir akarsuyun taşi{dotless}di{dotless}ǧi{dotless} aski{dotless}daki sediment miktari{dotless}ni{dotless}n pratik yoldan hesaplanmasi{dotless}. DSİ, Teknik Bülteni 94 (2000) 47-59 (in Turkish)
19. SubbaNarasimha P.N., Arinze B., and Anandarajan M. The predictive accuracy of artificial neural networks and multiple regression in the case of skewed data: exploration of some issues. Expert Systems with Applications 19 2 (2000) 117-123
20. Usha A.K. Comparison of neural networks and regression analysis: a new insight. Expert Systems with Applications 29 2 (2005) 424-430
21. van Rijn L.C. Sediment transport, Part 1: Bed load transport. Journal of Hydraulic Engineering, ASCE 110 (1984) 1431-1456
22. Wu W., Wang S.Y., and Yafei J. Nonuniform sediment transport in alluvial rivers. Journal of Hydraulic Research 38 (2000) 427-434
23. Zanke, U. (1978). Zusammenhange zwischen strömung und sediment transport, Mitt. Des Franzius- Instituts der Univ. Hannover, Nr. 47, Nr. 48 (in German).