Aiming to reduce the computational costs and converge to global optimum, a novel method is proposed to solve the optimization of a cost function in the estimation of direction of arrival （DOA）. In this method, a gen...Aiming to reduce the computational costs and converge to global optimum, a novel method is proposed to solve the optimization of a cost function in the estimation of direction of arrival （DOA）. In this method, a genetic algorithm （GA） and fuzzy discrete particle swarm optimization （FDPSO） are applied to optimize the direction of arrival and power parameters of the mode simultaneously. Firstly, the GA algorithm is applied to make the solution fall into the global searching. Secondly, the FDPSO method is utilized to narrow down the search field. In FDPSO, a chaotic factor and a crossover method are added to speed up the convergence. This approach has been demonstrated through some computational simulations. It is shown that the proposed algorithm can estimate both the DOA and the powers accurately. It is more efficient than some present methods, such as the Newton-like algorithm, Akaike information critical （AIC）, particle swarm optimization （PSO）, and genetic algorithm with particle swarm optimization （GA-PSO）.展开更多
In this work, the extractive distillation with heat integration process is extended to separate the pressure-insensitive benzene-cyclohexane azeotrope by using furfural as the entrainer. The optimal design of extracti...In this work, the extractive distillation with heat integration process is extended to separate the pressure-insensitive benzene-cyclohexane azeotrope by using furfural as the entrainer. The optimal design of extractive distillation process is established to achieve minimum energy requirement using the multi-objective genetic algorithm, and the results show that energy saving for this heat integration process is 15.7%. Finally, the control design is performed to investigate the system's dynamic performance, and three control structures are studied. The pressure-compensated temperature control scheme is proposed based on the first two control structures, and the dynamic responses reveal that the feed disturbances in both flow rate and benzene composition can be mitigated well.展开更多
With the development of laser technologies,multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms.A practical optimization algorithm ...With the development of laser technologies,multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms.A practical optimization algorithm is needed to generate such a waveform in order to control strong-field processes.We review some recent theoretical works of the optimization of amplitudes and phases of multi-color lasers to modify the single-atom high-order harmonic generation based on genetic algorithm.By choosing different fitness criteria,we demonstrate that：（i） harmonic yields can be enhanced by 10 to 100 times,（ii） harmonic cutoff energy can be substantially extended,（iii） specific harmonic orders can be selectively enhanced,and（iv） single attosecond pulses can be efficiently generated.The possibility of optimizing macroscopic conditions for the improved phase matching and low divergence of high harmonics is also discussed.The waveform control and optimization are expected to be new drivers for the next wave of breakthrough in the strong-field physics in the coming years.展开更多
In order to minimize the transmitted power in the multi-user orthogonal frequency division multiplexing（OFDM） system, a scheme combining the improved particle swarm optimization（POS） algorithm with genetic algori...In order to minimize the transmitted power in the multi-user orthogonal frequency division multiplexing（OFDM） system, a scheme combining the improved particle swarm optimization（POS） algorithm with genetic algorithm（GA） is proposed to optimize the sub-carriers and bits allocation. In the algorithm, a random velocity between the maximum and minimum particle velocity is used as the updating velocity instead of maximum or minimum velocity when the updated particle velocity is higher than the maximum particle velocity or lower than the minimum particle velocity. Then, the convergence population is used as the initial population of the genetic algorithm to optimize the subcarriers and bits allocation further. Simulation results show that the transmitted power of the proposed algorithm is about 2 d B to 10 d B lower than that of the genetic algorithm, particle swarm optimization algorithm, and Zhang＇s algorithm.展开更多
The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the to...The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the towing force of a vessel. A multi-objective genetic algorithm based on analytical models of the plow surface has been examined and applied in efforts to obtain optimal design of the plow. For a specific soil condition, the draft force and moldboard surface area which are the key parameters in the working process of the plow are optimized by finding the corresponding optimal values of the plow blade penetration angle and two surface angles of the main cutting blade of the plow. Parameters such as the moldboard side angle of deviation, moldboard lift angle, angular variation of the tangent line, and the spanning length are also analyzed with respect to the force of the moldboard surface along soil flow direction. Results show that the optimized plow has an improved plow performance. The draft forces of the main cutting blade and the moldboard are 10.6% and 7%, respectively, less than the original design. The standard deviation of Gaussian curvature of moldboard is lowered by 64.5%, which implies that the smoothness of the optimized moldboard surface is much greater than the original.展开更多
The us of stochastic resonance （SR） can effectively achieve the detection of weak signal in white noise and colored noise. However, SR in chaotic interference is seldom involved. In view of the requirements for the ...The us of stochastic resonance （SR） can effectively achieve the detection of weak signal in white noise and colored noise. However, SR in chaotic interference is seldom involved. In view of the requirements for the detection of weak signal in the actual project and the relationship between the signal, chaotic interference, and nonlinear system in the bistable system, a self-adaptive SR system based on genetic algorithm is designed in this paper. It regards the output signal-to-noise ratio （SNR） as a fitness function and the system parameters are jointly encoded to gain optimal bistable system parameters, then the input signal is processed in the SR system with the optimal system parameters. Experimental results show that the system can keep the best state of SR under the condition of low input SNR, which ensures the effective detection and process of weak signal in low input SNR.展开更多
文摘Aiming to reduce the computational costs and converge to global optimum, a novel method is proposed to solve the optimization of a cost function in the estimation of direction of arrival （DOA）. In this method, a genetic algorithm （GA） and fuzzy discrete particle swarm optimization （FDPSO） are applied to optimize the direction of arrival and power parameters of the mode simultaneously. Firstly, the GA algorithm is applied to make the solution fall into the global searching. Secondly, the FDPSO method is utilized to narrow down the search field. In FDPSO, a chaotic factor and a crossover method are added to speed up the convergence. This approach has been demonstrated through some computational simulations. It is shown that the proposed algorithm can estimate both the DOA and the powers accurately. It is more efficient than some present methods, such as the Newton-like algorithm, Akaike information critical （AIC）, particle swarm optimization （PSO）, and genetic algorithm with particle swarm optimization （GA-PSO）.
基金supported by the National Natural Science Foundation of China(grant number 21476261)the Key Research and Development Plan Project of Shandong Province(grant number 2015GGX107004)
文摘In this work, the extractive distillation with heat integration process is extended to separate the pressure-insensitive benzene-cyclohexane azeotrope by using furfural as the entrainer. The optimal design of extractive distillation process is established to achieve minimum energy requirement using the multi-objective genetic algorithm, and the results show that energy saving for this heat integration process is 15.7%. Finally, the control design is performed to investigate the system's dynamic performance, and three control structures are studied. The pressure-compensated temperature control scheme is proposed based on the first two control structures, and the dynamic responses reveal that the feed disturbances in both flow rate and benzene composition can be mitigated well.
基金Project supported by the Fundamental Research Funds for the Central Universities of China(Grant No.30916011207)Chemical Sciences,Geosciences and Biosciences Division,Office of Basic Energy Sciences,Office of Science,U.S.Department of Energy(Grant No.DE-FG02-86ER13491)Air Force Office of Scientific Research,USA(Grant No.FA9550-14-1-0255)
文摘With the development of laser technologies,multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms.A practical optimization algorithm is needed to generate such a waveform in order to control strong-field processes.We review some recent theoretical works of the optimization of amplitudes and phases of multi-color lasers to modify the single-atom high-order harmonic generation based on genetic algorithm.By choosing different fitness criteria,we demonstrate that：（i） harmonic yields can be enhanced by 10 to 100 times,（ii） harmonic cutoff energy can be substantially extended,（iii） specific harmonic orders can be selectively enhanced,and（iv） single attosecond pulses can be efficiently generated.The possibility of optimizing macroscopic conditions for the improved phase matching and low divergence of high harmonics is also discussed.The waveform control and optimization are expected to be new drivers for the next wave of breakthrough in the strong-field physics in the coming years.
基金supported by the National Natural Science Foundation of China under Grant No.61371112
文摘In order to minimize the transmitted power in the multi-user orthogonal frequency division multiplexing（OFDM） system, a scheme combining the improved particle swarm optimization（POS） algorithm with genetic algorithm（GA） is proposed to optimize the sub-carriers and bits allocation. In the algorithm, a random velocity between the maximum and minimum particle velocity is used as the updating velocity instead of maximum or minimum velocity when the updated particle velocity is higher than the maximum particle velocity or lower than the minimum particle velocity. Then, the convergence population is used as the initial population of the genetic algorithm to optimize the subcarriers and bits allocation further. Simulation results show that the transmitted power of the proposed algorithm is about 2 d B to 10 d B lower than that of the genetic algorithm, particle swarm optimization algorithm, and Zhang＇s algorithm.
基金Supported the National Natural Science Foundation of China （No. 51179040） Natural Science Foundation of Heilongjiang Province （No. E200904）
文摘The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the towing force of a vessel. A multi-objective genetic algorithm based on analytical models of the plow surface has been examined and applied in efforts to obtain optimal design of the plow. For a specific soil condition, the draft force and moldboard surface area which are the key parameters in the working process of the plow are optimized by finding the corresponding optimal values of the plow blade penetration angle and two surface angles of the main cutting blade of the plow. Parameters such as the moldboard side angle of deviation, moldboard lift angle, angular variation of the tangent line, and the spanning length are also analyzed with respect to the force of the moldboard surface along soil flow direction. Results show that the optimized plow has an improved plow performance. The draft forces of the main cutting blade and the moldboard are 10.6% and 7%, respectively, less than the original design. The standard deviation of Gaussian curvature of moldboard is lowered by 64.5%, which implies that the smoothness of the optimized moldboard surface is much greater than the original.
基金Project supported by the National Natural Science Foundation of China(Grant No.61271011)
文摘The us of stochastic resonance （SR） can effectively achieve the detection of weak signal in white noise and colored noise. However, SR in chaotic interference is seldom involved. In view of the requirements for the detection of weak signal in the actual project and the relationship between the signal, chaotic interference, and nonlinear system in the bistable system, a self-adaptive SR system based on genetic algorithm is designed in this paper. It regards the output signal-to-noise ratio （SNR） as a fitness function and the system parameters are jointly encoded to gain optimal bistable system parameters, then the input signal is processed in the SR system with the optimal system parameters. Experimental results show that the system can keep the best state of SR under the condition of low input SNR, which ensures the effective detection and process of weak signal in low input SNR.
