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- W2357708272 abstract "Genetic algorithm for harmonic balance simulation often appear randomness,the iterative process is slow,weak local search capabilities and other issues,this paper proposed an improved hybrid genetic algorithm. The algorithm combined with Volterra series method,genetic algorithm and the quasi-Newton algorithm. Firstly,it used the characteristics of the memory of Volterra series to estimate the initial value of frequency domain,and then by means of genetic algorithm for global optimization,and finally used the quasi-Newton algorithm for local optimization. Based on the MRF281 harmonic balance simulation results show that the algorithm and genetic algorithm,the number of iterations reduced by 40%,while the simulation data and measured data fitting better. Algorithm combines the global optimization and local optimization features,significantly improves the harmonic balance equations accuracy and convergence rate,and to overcome the randomness of genetic algorithms,local search ability is weak and other shortcomings,the nonlinear circuit analysis has great reference value." @default.
- W2357708272 created "2016-06-24" @default.
- W2357708272 creator A5058260592 @default.
- W2357708272 date "2014-01-01" @default.
- W2357708272 modified "2023-09-23" @default.
- W2357708272 title "Application of improved hybrid genetic algorithm based on Volterra series to harmonic balance" @default.
- W2357708272 hasPublicationYear "2014" @default.
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