Simulation of Standing and Propagating Sea Waves . . .
277
The future work is to make ARMA mathematical apparatus and its numerical
implementation a base of virtual testbed for marine objects dynamics studies.
References
1. St. Denis, M., & Pierson, W. J., Jr. (1953). On the motions of ships in confused seas. Technical
report, New York University, Bronx School of Engineering and Science
2. Rosenblatt, M. (1956). A random model of the sea surface generated by a hurricane. Technical
report, DTIC Document
3. Sveshnikov, A. A. (1959). Mathematics Akademii Mechanics and Engineering, 3, 32.
4. Longuet-Higgins, M. S. (1957). Philosophical Transactions of the Royal Society of London A:
Mathematical, Physical and Engineering Sciences, 249(966), 321.
5. Kochin, N., Kibel, I., & Roze, N. (1966). Theoretical hydrodynamics (in Russian). FizMatLit.
6. Beck, R. F., Reed, A. M., Sclavounos, P. D., & Hutchison, B. L. (2001). Transactions-Society
of Naval Architects and Marine Engineers, 109, 1.
7. Box, G. E., & Jenkins, G. M. (1976). Time series analysis: Forecasting and control (revised
ed.). Holden-Day.
8. Kostecki, M. (1972). Stochastic model of sea waves. Ph.D. thesis, CTO, Gdansk.
9. Rozhkov, V. A., & Trapeznikov, Y. A. (1990). Probabilistic models of oceanographic processes. Leningrad: Gidrometeoizdat.
10. Gurgenidze, A. T., & Trapeznikov, Y. A. (1988). Probabilistic model of wind waves (pp. 8–23).
Leningrad: Gidrometeoizdat.
11. Spanos, P. D. (1982). ARMA algorithms for ocean spectral analysis. University of Texas at
Austin, Engineering Mechanics Research Laboratory.
12. Spanos, P. D., & Zeldin, B. (1996). Earthquake Engineering and Structural Dynamics, 25(5),
497.
13. Fusco, F., & Ringwood, J. V. (2010). IEEE Transactions on Sustainable Energy, 1(2), 99.
14. Degtyarev, A., & Gankevich, I. (2012). Proceedings of 11th International Conference on Stability of Ships and Ocean Vehicles, Athens (pp. 841–852)
15. Degtyarev, A. B., & Podoliakin, A. B. (1998). Proceedings of II International Conferences on
Shipbuilding (ISC’98), Saint-Petersburg (Vol. V, pp. 416–423).
16. Degtyarev, A., & Boukhanovsky, A. (1997). Analysis of peculiarities of ship-environmental
interaction. Technical report, 09-97-1AB-1VA, Strathclyde University, Ship Stability Research
Center, Glasgow.
17. Boccotti, P. (1983). Meccanica, 18(4), 205.
18. Degtyarev, A. B., & Reed, A. M. (2011). Proceedings of the 12th International Ship Stability
Work-shop.
19. Degtyarev, A. B., & Reed, A. M. (2013). International Shipbuilding Progress, 60(1–4), 523.
20. Boukhanovsky, A. V. (1997). Probabilistic modeling of wind wave fields taking into account
their heterogeneity and nonstationarity. Ph.D. thesis, Saint Petersburg State University.
21. Wolfram Research Inc. (2016). Mathematica. Champaign, Illinois.
22. Matsumoto, M., & Nishimura, T. (1998). ACM Transactions on Modeling and Computer Simulation (TOMACS), 8(1), 3.
23. Matsumoto, M., & Nishimura, T. (1998). Monte Carlo and Quasi-Monte Carlo Methods, 2000,
56.
24. Oppenheim, A. V., Schafer, R. W., Buck, J. R., et al. (1989). Discrete-time signal processing
(Vol. 2). Englewood Cliffs, NJ: Prentice Hall.
25. Svoboda, D. (2011). Image Analysis and Processing–ICIAP 2011 (pp. 453–462). Springer.
26. Pavel, K., & David, S. (2013). Algorithms for efficient computation of convolution. INTECH
Open Access Publisher.
277
The future work is to make ARMA mathematical apparatus and its numerical
implementation a base of virtual testbed for marine objects dynamics studies.
References
1. St. Denis, M., & Pierson, W. J., Jr. (1953). On the motions of ships in confused seas. Technical
report, New York University, Bronx School of Engineering and Science
2. Rosenblatt, M. (1956). A random model of the sea surface generated by a hurricane. Technical
report, DTIC Document
3. Sveshnikov, A. A. (1959). Mathematics Akademii Mechanics and Engineering, 3, 32.
4. Longuet-Higgins, M. S. (1957). Philosophical Transactions of the Royal Society of London A:
Mathematical, Physical and Engineering Sciences, 249(966), 321.
5. Kochin, N., Kibel, I., & Roze, N. (1966). Theoretical hydrodynamics (in Russian). FizMatLit.
6. Beck, R. F., Reed, A. M., Sclavounos, P. D., & Hutchison, B. L. (2001). Transactions-Society
of Naval Architects and Marine Engineers, 109, 1.
7. Box, G. E., & Jenkins, G. M. (1976). Time series analysis: Forecasting and control (revised
ed.). Holden-Day.
8. Kostecki, M. (1972). Stochastic model of sea waves. Ph.D. thesis, CTO, Gdansk.
9. Rozhkov, V. A., & Trapeznikov, Y. A. (1990). Probabilistic models of oceanographic processes. Leningrad: Gidrometeoizdat.
10. Gurgenidze, A. T., & Trapeznikov, Y. A. (1988). Probabilistic model of wind waves (pp. 8–23).
Leningrad: Gidrometeoizdat.
11. Spanos, P. D. (1982). ARMA algorithms for ocean spectral analysis. University of Texas at
Austin, Engineering Mechanics Research Laboratory.
12. Spanos, P. D., & Zeldin, B. (1996). Earthquake Engineering and Structural Dynamics, 25(5),
497.
13. Fusco, F., & Ringwood, J. V. (2010). IEEE Transactions on Sustainable Energy, 1(2), 99.
14. Degtyarev, A., & Gankevich, I. (2012). Proceedings of 11th International Conference on Stability of Ships and Ocean Vehicles, Athens (pp. 841–852)
15. Degtyarev, A. B., & Podoliakin, A. B. (1998). Proceedings of II International Conferences on
Shipbuilding (ISC’98), Saint-Petersburg (Vol. V, pp. 416–423).
16. Degtyarev, A., & Boukhanovsky, A. (1997). Analysis of peculiarities of ship-environmental
interaction. Technical report, 09-97-1AB-1VA, Strathclyde University, Ship Stability Research
Center, Glasgow.
17. Boccotti, P. (1983). Meccanica, 18(4), 205.
18. Degtyarev, A. B., & Reed, A. M. (2011). Proceedings of the 12th International Ship Stability
Work-shop.
19. Degtyarev, A. B., & Reed, A. M. (2013). International Shipbuilding Progress, 60(1–4), 523.
20. Boukhanovsky, A. V. (1997). Probabilistic modeling of wind wave fields taking into account
their heterogeneity and nonstationarity. Ph.D. thesis, Saint Petersburg State University.
21. Wolfram Research Inc. (2016). Mathematica. Champaign, Illinois.
22. Matsumoto, M., & Nishimura, T. (1998). ACM Transactions on Modeling and Computer Simulation (TOMACS), 8(1), 3.
23. Matsumoto, M., & Nishimura, T. (1998). Monte Carlo and Quasi-Monte Carlo Methods, 2000,
56.
24. Oppenheim, A. V., Schafer, R. W., Buck, J. R., et al. (1989). Discrete-time signal processing
(Vol. 2). Englewood Cliffs, NJ: Prentice Hall.
25. Svoboda, D. (2011). Image Analysis and Processing–ICIAP 2011 (pp. 453–462). Springer.
26. Pavel, K., & David, S. (2013). Algorithms for efficient computation of convolution. INTECH
Open Access Publisher.