By Robert Klaßen
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Evol. Comput. 9(6), 721–735 (2005) 33. J. Liu, S. Zheng, Y. Tan, Analysis on global convergence and timecomplexity of fireworks algorithm, in IEEE Congress on Evolutionary Computation (CEC’2014) (Beijing, China, 2014), pp. 3207–3213 34. K. Ding, S. Zheng, Y. Tan. A GPU-based parallel fireworks algorithm for optimization. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation Conference (ACM, The Netherlands, 2013), pp. 9–16 35. Y. Pei, S. Zheng, Y. Tan, H. Takagi, An empirical study on influence of approximation approaches on enhancing fireworks algorithm, in Proceedings of the 2012 IEEE Congress on System, Man and Cybernetics (IEEE, 2012), pp.
B S-metric for a solution. . . . . . . . . . . . . . S-metric. a Calculation of S-metric. b The increase of neighbors’ S-metric after wiping away a solution . MOFWA evolution process on KUR. a Iteration = 10. b Iteration = 20. c Iteration = 250. d Iteration = 300 . . . . . . . . . . . . . . . . . Plots of the final archive of returned by S-MOFWA in the objective space. a ZDT1. b ZDT2. c ZDT3. d SCH. e KUR. f ZDT6 . . . . . . . . . . Framework of discrete FWA .
Simulations were carried out on well-known IEEE 33- and 69-bus test systems at three different load levels to demonstrate well the performance and effectiveness of the proposed FWA method. Recently, in , R. Rajaram et al. presented their latest work of selective harmonic elimination in PWM inverter using fireworks algorithm in which a slightly modified FWA and firefly were used to solve the selective harmonic elimination problem in inverter output waveforms. It turns out from experiments that the FWA works faster than modified firefly algorithm as well as other popular algorithms of ant colony, PSO, and GA.
Adobe Premiere Pro CS3. Das Praxisbuch mit zahlreichen Workshops by Robert Klaßen
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