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All issues Volume 564 (2024) E3S Web Conf., 564 (2024) 11007 References
Open Access
Issue
E3S Web Conf.
Volume 564, 2024
International Conference on Power Generation and Renewable Energy Sources (ICPGRES-2024)
Article Number 11007
Number of page(s) 12
Section Power Engineering and Materials
DOI https://doi.org/10.1051/e3sconf/202456411007
Published online 06 September 2024
  1. N.M. Alexandrov. A trust region framework for managing approximation models in engineering optimization. In 6th AIAA/NASA/ ISSMO Symp. on Multidisciplinary Analysis and Opt., (1996) [Google Scholar]
  2. N.M. Alexandrov, R.M. Lewis, C.R. Gumbert, L.L. Green, P.A. Newman. Optimization with variable-fidelity models applied to wing design. In: 38th Aerospace Sciences Meeting & Exhibit, Reno, USA, (2000) [Google Scholar]
  3. N.M. Alexandrov, R.M. Lewis. First-order approximation and model management in optimization. In: L.T. Biegler, O. Ghattas, M. Heinkenschloss, B. van Bloemen Waanders (Eds.), Large-Scale PDE-Constrained Optimization, Lecture notes in Computational Science and Engineering, Springer, (2003) [Google Scholar]
  4. L.T. Biegler, O. Ghattas, M. Heinkenschloss, B. Van Bloemen Waanders (Eds.). Large-Scale PDE-Constrained Optimization. Lecture notes in Computational Science and Engineering, Springer, (2003) [CrossRef] [Google Scholar]
  5. C. Bischof, A. Carle, G. Corliss, A. Grienwank, P. Hovland. ADIFOR: generating derivative codes from Fortran programs. Sci. Programm., 1, 1, 11–29, (1992) [Google Scholar]
  6. E.F. Campana, D. Peri, A. Pinto, F. Stern, Y. Tahara. A comparison of global optimization methods with application to ship design. In: 5th Osaka Coll. on Advanced CFD Applications to Ship Flow and Hull Form Design, Osaka, Japan, (2005) [Google Scholar]
  7. K.J. Chang, R.T. Haftka, G.L. Giles, P.J. Kao. Sensitivity-based scaling for approximating structural response. J. Aircraft, 30, 2, 283–288, (1993) [CrossRef] [Google Scholar]
  8. S.E. Cox, R.T. Haftka, C.A. Baker, B. Grossman, W.H. Mason, L.T. Watson. A comparison of global optimization methods for the design of a high-speed civil transport. J. Global Optimiz., 21, 415–433, (2001) [CrossRef] [Google Scholar]
  9. H.W. Coleman, F. Stern. Uncertainties in CFD code validation. ASME J. Fluids Engrg., 119, 795–803, (1997) [CrossRef] [Google Scholar]
  10. L. Davis. Handbook of Genetic Algorithms, Van Nostrand Reinhold, A Division of Wadsworth, Inc., (1990) [Google Scholar]
  11. A. Di Mascio, R. Broglia, B. Favini. A second-order Godunov-type scheme for Naval Hydrodynamics. In: Godunov Methods: Theory and Application, Kluwer Academic Publishers, Singapore, (2000) [Google Scholar]
  12. R. Duvigneau, M. Visonneau. Hybrid genetic algorithms and artificial neural networks for complex design optimisation in CFD. Int. J. Numer. Methods Fluids, 44, 1257–1278, (2004) [CrossRef] [Google Scholar]
  13. R. Giering, T. Kaminski. Recipes for adjoint code construction. ACM Trans. Math. Software, 24, 4, 437–474, (1998) [CrossRef] [Google Scholar]
  14. Gothenburg. https://www.iihr.uiowa.edu/gothenburg2000, (2000) [Google Scholar]
  15. A. Griewank. Evaluating derivatives: Principles and Techniques of Algorithmic Differentiation. SIAM, Philadelphia, USA, (2000) [Google Scholar]
  16. R.T. Haftka. Combining global and local approximations. AIAA J., 29, 1523–1525, (1991) [CrossRef] [Google Scholar]
  17. J. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, USA, (1975) [Google Scholar]
  18. A. Jameson. Aerodynamic design via control theory. J. Sci. Comput., 3, 233–260, (1988) [CrossRef] [Google Scholar]
  19. L. Larsson, F. Stern, V. Bertram. Benchmarking of computational fluid dynamics for ship flows: The Gothenburg 2000 Workshop. J. Ship Res., 47, 1, 63–81, (2003) [CrossRef] [Google Scholar]
  20. W.G. Meyers, T.R. Applebee, A.E. Baitis. User’s Manual for the Standard Ship Motion Program, SMP (No. DTNSRDC/SPD-0936-01), (1981) [Google Scholar]
  21. D. Peri, E.F. Campana. High-fidelity models and multiobjective global optimization algorithms in simulation based design. J. Ship Res., 49, 3, 159–175, (2005) [CrossRef] [Google Scholar]
  22. O. Pironneau. Optimal Shape Design for Elliptic Systems. Springer Verlag, New York, USA, (1984) [CrossRef] [Google Scholar]
  23. P.R. Spalart, S.R. Allmaras. One-equation turbulence model for aerodynamic flows. J. Aerosp. Res., 1, 5–21, (1994) [Google Scholar]
  24. Athambawa, A., Johar, M. G. M., & Khatibi, A. (2023b). Behavioural intention to adopt cloud computing: A quantitative analysis with a mediatory factor using bootstrapping. Indonesian Journal of Electrical Engineering and Computer Science, 32(1), 458–467. https://doi.org/10.11591/ijeecs.v32.i1.pp458-467 [CrossRef] [Google Scholar]
  25. Athambawa, A., Md Johar, M. G., & Khathibi, A. (2022). Secure cloud adoption model: novel hybrid reference model. Indonesian Journal of Electrical Engineering and Computer Science, 27(2), 936–943. https://doi.org/10.11591/ijeecs.v27.i2.pp936-943 [CrossRef] [Google Scholar]
  26. Dissanayake, K., & Johar, M. G. M. (2021). Comparative study on heart disease prediction using feature selection techniques on classification algorithms. Applied Computational Intelligence and Soft Computing, 2021. https://doi.org/10.1155/2021/5581806 [Google Scholar]

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