Genetic programming for retrieving missing information in wave records along the west coast of India

Applied Ocean Research

Volumn 29, Issue 3, 2007, Pages 99-111

  Kalra, Ruchi ^a   Deo, M C ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

ANN; GP; Missing data; Soft computing; Wave heights

Indexed keywords

BUOYS; COASTAL ZONES; ERROR STATISTICS; GENETIC PROGRAMMING; INFORMATION RETRIEVAL SYSTEMS; MEAN SQUARE ERROR; SOFT COMPUTING;

CORRELATION COEFFICIENT; SCATTER INDEX; WAVE HEIGHT;

WATER WAVES;

BUOYS; COASTAL ZONES; ERROR STATISTICS; GENETIC PROGRAMMING; INFORMATION RETRIEVAL SYSTEMS; MEAN SQUARE ERROR; SOFT COMPUTING; WATER WAVES;

ARTIFICIAL NEURAL NETWORK; ERROR ANALYSIS; NUMERICAL METHOD; STATISTICAL ANALYSIS; WATER WAVE; WAVE HEIGHT;

INDIAN OCEAN; INDIAN OCEAN (WEST);

EID: 39549110229     PISSN: 01411187     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apor.2007.11.002     Document Type: Article

References (29)

1. Balas C.N., Koc L., and Balas L. Predictions of missing wave data by recurrent neuronets. Journal of Waterway, Port, Coastal and Ocean Engineering, ASCE 130 5 (2004) 256-265
2. Bennis S., Berrada F., and Kang N. Improving single variable and multi-variable techniques for estimating missing hydrological data. Journal of Hydrology 191 (1997) 87-105
3. Babovic V., Kanizares R., Jenson H.R., and Klinting A. Neural networks as routine for error updating of numerical models. Journal of Hydraulic Engineering, ASCE 127 3 (2001) 181-193
4. Babovic V., Drecourt J.P., Keijzer M., and Hansen P.F. A data mining approach to modeling of water supply assets. Urban Water 4 (2002) 401-414
5. Babovic V, Keijzer M, Aguilera DR, Harrington J. An evolutionary approach to knowledge induction: Genetic programming in hydraulic engineering. In: ASCE conference proceedings. 2004
6. Demuth H., Beale M., and Hagen M. Neural network toolbox user's guide (1998), The Mathworks Inc., Natick (MA, USA)
7. Drecourt JP. Application of neural networks and genetic programming to rainfall runoff modeling. Danish Hydraulic Institute, Hydro-Informatics Techonologies HIT, 1999, June, D2K-0699-1
8. Drunpob A., Chang N.B., and Beaman M. Stream flow rate prediction using genetic programming model in a semi-arid coastal watershed. Proceedings of EWRI (2005), ASCE
9. Elshorbagy A., Simonovic S.P., and Panu U.S. Estimation of missing streamflow data using principles of chaos theory. Journal of Hydrology 255 (2002) 123-133
10. Emery W.J., and Thomson R.S. Data analysis methods in physical oceanography (2004), Elsevier publication
11. Francone FD. Discipulus owner's manual. Littleton (CO); Machine Learning Technologies, Inc.; 1998
12. Fonlupt C. Solving the ocean color problem using a genetic programming approach. Applied Soft Computing 1 (2001) 63-72
13. Hong Y.S., and Rao B. Evolutionary self-organizing modeling of a municipal wastewater treatment plant. Water Research 37 (2003) 1199-1212
14. Hong Y.S., and Rosen M.R. Identification of an urban fractured-rock aquifer dynamics using an evolutionary self-organizing modeling. Journal of Hydrology 259 (2002) 89-104
15. Kalra R., Deo M.C., Kumar R., and Aggarwal V.K. Artificial neural network to translate offshore satellite wave data to coastal locations. Ocean Engineering, Elsevier 32 16 (2005) 1917-1932
16. Keijzer M, Baptist M, Babovic V, Collet P, Uthurburu. Genetic and evolutionary computation conference proceedings of the 2005 conference on Genetic and evolutionary computation. Washington (DC, USA): 1999-2006
17. Khalil M., Panu U.S., and Lennox W.C. Groups and neural networks based streamflow data in-filling procedures. Journal of Hydrology 241 (2001) 153-176
18. Koza J.R. Genetic programming: On the programming of computers by means of natural selection. A Bradford Book (1992), MIT Press
19. Makarynskyy O., Makarynska D., Rusu E., and Gavrilov A. Filling gaps in wave records with artificial neural networks. In: Guedes Soares C., Garbatov Y., and Fonseca N. (Eds). Maritime transportation and exploitation of ocean and coastal resources (2005), Taylor & Francis Group, London 1085-1091
20. Makarynskyy O., Makarynska D., Kuhn M., and Featherstone W.E. Using artificial neural networks to estimate sea level in continental and island coastal environments. In: Cheng L., and Yeow K. (Eds). Hydrodynamics IV: Theory and applications (2005), Taylor & Francis Group, London 451-457
21. Makarynskyy O., and Makarynska D. Wave prediction and data supplementation using artificial neural networks. Journal of Coastal Research 23 4 (2007) 951-960
22. Mutreja K.N. Applied hydrology (1987), Tata McGraw-Hill publications
23. Muttil N, Liong SY. Improving runoff forecasting by input variable selection in genetic programming. In: Proceedings of world water congress. ASCE, Downloaded 04 Aug 2005 from http://www.ascelibrary.org/; 2004
24. Puca S, Tirozzi B, Arena G, Corsini S, Inghilesi R. A neural network approach to the problem of recovering lost data in a network of marine buoys. In: Proceedings of international society of offshore and polar engineers. 2001, vol. III, 2001. p. 615-20
25. Stefanakos C.N., and Athanassoulis G.A. A unified methodology for the analysis, completion and simulation of nonstationary time series with missing values, with application to wave data. Applied Ocean Research 23 4 (2001) 207-220
26. Sturges W. On interpolating gappy records for time series analysis. Journal of Geophysical Research 88 (1983) 9736-9740
27. Thompson R. Spectral estimation from irregularly spaced data. IEEE Transaction on Geoscience Electronics GE-9 (1971) 107-119
28. Ustoorikar K., and Deo M.C. Filling up gaps in wave height time series using genetic programming, under consideration in marine structures (2007), Elsevier
29. Whigham PA, Crapper PF. Modeling rainfall-runoff using genetic programming. In: Mathematical and Computer Modeling 33. Canberra (Australia); 2001, p. 707-21