المؤلفون: Neshat, M., Sergiienko, N. Y., Majidi Nezhad, Meysam, da Silva, L. S. P., Amini, E., Marsooli, R., Astiaso Garcia, D., Mirjalili, S.

المصدر: Applied Energy. 362

مصطلحات موضوعية: Genetic algorithms, Hybrid wave-wind energy systems, Multi-objective optimisation algorithm, Offshore wind turbine, Sustainable energy, Swarm-intelligence algorithms, Wave energy converters, Australia, Offshore oil well production, Offshore wind turbines, Power quality, Power takeoffs, Wave energy conversion, Wind power, Hybrid wave-wind energy system, Hybrid waves, Multi-objective optimization algorithm, Multi-objectives optimization, Optimization algorithms, Swarm intelligence algorithms, Wave wind, Wind energy systems, acceleration, damping, wave energy, wind turbine, Multiobjective optimization

وصف الملف: print

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-66338Test
https://doi.org/10.1016/j.apenergy.2024.122955Test

المؤلفون: Helbig, M, Engelbrecht, AP

مصطلحات موضوعية: Dynamic multi-objective optimisation problems, DMOOP, Dynamic multi-objective optimisation algorithm, DMOA

وصف الملف: application/pdf

العلاقة: Workflow;11367; Helbig, M and Engelbrecht, A.P. 2013. Analysing the performance of dynamic multi-objective optimisation algorithms. In: 2013 IEEE Congress on Evolutionary Computation, 20-23 June 2013, Cancún, México; http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6557744Test; http://hdl.handle.net/10204/6945Test

الإتاحة: http://hdl.handle.net/10204/6945Test
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6557744Test