Genetic programming for real-time prediction of offshore wind

Ships and Offshore Structures

Volumn 4, Issue 1, 2009, Pages 77-88

  Charhate, S B ^a   Deo, M C ^a   Londhe, S N ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

Artificial neural networks; Genetic programming; Wind direction; Wind prediction; Wind speed

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; COMPUTING DOMAINS; FLOATING BUOYS; GENETIC OPERATORS; MODELLING TOOLS; OFFSHORE ENGINEERINGS; OFFSHORE LOCATIONS; OFFSHORE WINDS; PROBLEM DOMAINS; REAL-TIME PREDICTIONS; SOFT-COMPUTING TOOLS; SPATIAL CORRELATIONS; WEST COASTS; WIND DIRECTION; WIND MEASUREMENTS; WIND PREDICTION; WIND SPEED;

APPLICATIONS; BACKPROPAGATION; COMPUTER PROGRAMMING; ENGINEERING RESEARCH; FISCHER-TROPSCH SYNTHESIS; SOFT COMPUTING; WIND EFFECTS;

NEURAL NETWORKS;

EID: 77949664611     PISSN: 17445302     EISSN: None     Source Type: Journal    
DOI: 10.1080/17445300802492638     Document Type: Article

References (14)

1. Cadenas, E. and Rivera, W. (2007) Wind speed forecasting in the South Coast of Oaxaca, Mexico. Journal of Renewable Energy, 32, pp. 2116-2128.
2. Charhate, SB, Deo, MC and SanilKumar, V. (2007) Soft and hard computing approaches for real-time prediction of coastal currents in a tide dominated area. Proceedings of the Institution of Mechanical Engineers. Journal of Engineering for the Maritime Environment, 221, pp. 147-163.
3. Cornford, D., Nabney, IT and Bishopa, CM (1999) Neural network-based wind vector retrieval from satellite scatterometer data, pp. 1-16. Neural Network Computing Group. Technical Report NCRG-99/003, Birmingham, UK
4. Drecourt, JP (1999) Application of neural networks and genetic programming to rainfall runoff modeling, Danish Hydraulic Institute (Hydro-Informatics Technologies HIT), Denmark
5. Fancone, FD (1998) Discipulus owner's manual. Littleton (CO), Machine Learning Technologies, Inc. F.D.
6. Hong, YS and Rao, B. (2003) Evolutionary self-organizing modeling of a municipal wastewater treatment plant. Journal of Water Research, 37:6, pp. 1199-1212.
7. Koza, JR (1992) Genetic programming: On the programming of computers by means of natural selection, Bradford Book, MIT Press, Cambridge, MA
8. More, A. and Deo, MC (2003) Forecasting wind with neural networks. Journal of Marine Structures, 16, pp. 35-49.
9. Muttil, N. and Liong, SY (2004) A superior exploration-exploitation balance in shuffled complex evolution. ASCE Journal of Hydraulic Engineering, 130:12, pp. 1202-1205.
10. Kalra, R. and Deo, MC (2008) Genetic programming to retrieve missing information in wave records along the west coast of India. Applied Ocean Research, 29:3, pp. 99-111.
11. Thiria, SC, Badran, MF and Crepon, M. (1993) A neural network approach for modeling nonlinear transfer functions: Application for wind retrieval from space-borne scatterometer data. Journal of Geophysical Research, 98, pp. 827-841.
12. Thirumalaiah, K. and Deo, MC (1998) River stage forecasting using neural networks. ASCE Journal of Hydrological Engineering, 3:1, pp. 26-32.
13. Whigham, PA and Crapper, PF (2001) Modeling rainfall-runoff using genetic programming. Mathematical and Computer Modeling, 33, pp. 707-721. Canberra, Australia
14. Zhang, GP (2003) Time series forecasting using a hybrid ARIMA and neural network model. Journal of Neuro Computing, 50, pp. 159-175.