This paper proposes an improved Gaussian particle filter integratingthe Artificial Fish School Algorithm to optimise the measured values to improve the overall estimation accuracy of the system.Meanwhile,it also solve...This paper proposes an improved Gaussian particle filter integratingthe Artificial Fish School Algorithm to optimise the measured values to improve the overall estimation accuracy of the system.Meanwhile,it also solves the problems of susceptibility to interference and insufficient estimation accuracy in nonlinear systems.Furthermore,since the calculation time of the fusion algorithm increases,in order to ensure the speed of state estimation,the linear transformation of standard particle swarm is used to replace the particle sampling link of Gaussian particle filter.Simulation results show that the calculation speed of a fast Gaussian Particle Filter based on the Artificial Fish School Algorithm is 21.7%faster than the Particle Filter based on the Artificial Fish School Algorithm.Compared with Particle Filter,Gaussian particle filter,and the Artificial Fish School Algorithm,the proposed algorithm has a higher accuracy.展开更多
Numerical simulations of self-propelled swimming of a three dimensional bionic fish and fish school in a viscous fluid are carried out. This is done with the assistance of a parallel software package produced for 3D m...Numerical simulations of self-propelled swimming of a three dimensional bionic fish and fish school in a viscous fluid are carried out. This is done with the assistance of a parallel software package produced for 3D moving boundary problems. This computational fluid dynamics package combines the adaptive multi-grid finite volume method, the immersed boundary method and VOF (volume of fluid) method. By using the package results of the self-propelled swimming of a 3D bionic fish and fish school in a vis- cous fluid are obtained. With comparison to the existing experimental measurements of living fishes, the predicted structure of vortical wakes is in good agreement with the measurements.展开更多
为提高智能机器人的路径寻优能力,文章提出一种基于检测算子和经验学习的鱼群算法(Detection Operator and Experiecnce Learning Artificial Fish Swarm Algorithm,DOEL-AFSA)。仿真实验结果表明,DOEL-AFSA得到的最短路径比鱼群算法(AF...为提高智能机器人的路径寻优能力,文章提出一种基于检测算子和经验学习的鱼群算法(Detection Operator and Experiecnce Learning Artificial Fish Swarm Algorithm,DOEL-AFSA)。仿真实验结果表明,DOEL-AFSA得到的最短路径比鱼群算法(AFSA)、动态分级蚁群算法(WAS)等算法更好,其求解效率更高。展开更多
基金supported by Aeronautical Science Founda-tion of China[grant numbers 2018ZC52037,2017ZC52017]and National Natural Science Foundation of China[grant number 51505221].
文摘This paper proposes an improved Gaussian particle filter integratingthe Artificial Fish School Algorithm to optimise the measured values to improve the overall estimation accuracy of the system.Meanwhile,it also solves the problems of susceptibility to interference and insufficient estimation accuracy in nonlinear systems.Furthermore,since the calculation time of the fusion algorithm increases,in order to ensure the speed of state estimation,the linear transformation of standard particle swarm is used to replace the particle sampling link of Gaussian particle filter.Simulation results show that the calculation speed of a fast Gaussian Particle Filter based on the Artificial Fish School Algorithm is 21.7%faster than the Particle Filter based on the Artificial Fish School Algorithm.Compared with Particle Filter,Gaussian particle filter,and the Artificial Fish School Algorithm,the proposed algorithm has a higher accuracy.
基金Supported by the Key Project of National Natural Science Foundation of China (Grant No. 10532040)
文摘Numerical simulations of self-propelled swimming of a three dimensional bionic fish and fish school in a viscous fluid are carried out. This is done with the assistance of a parallel software package produced for 3D moving boundary problems. This computational fluid dynamics package combines the adaptive multi-grid finite volume method, the immersed boundary method and VOF (volume of fluid) method. By using the package results of the self-propelled swimming of a 3D bionic fish and fish school in a vis- cous fluid are obtained. With comparison to the existing experimental measurements of living fishes, the predicted structure of vortical wakes is in good agreement with the measurements.
文摘为提高智能机器人的路径寻优能力,文章提出一种基于检测算子和经验学习的鱼群算法(Detection Operator and Experiecnce Learning Artificial Fish Swarm Algorithm,DOEL-AFSA)。仿真实验结果表明,DOEL-AFSA得到的最短路径比鱼群算法(AFSA)、动态分级蚁群算法(WAS)等算法更好,其求解效率更高。
文摘中西太平洋热带海域是世界上最大的鲣(Katsuwonus pelamis)渔场。为合理开发和利用中西太平洋围网鲣自由鱼群的渔业资源,根据1995—2019年中西太平洋渔业委员会的围网鲣数据计算资源丰度指数,得出渔场重心,并结合海表温度(Sea surface temperature,SST)、海洋尼诺指数(Oceanic Niño Index,ONI)进行皮尔森相关性分析。结果显示,单位捕捞努力量渔获量(Catch per unit effort,CPUE)可用于表征自由鱼群渔场重心的资源丰度,且与暖池重心经度以及右边缘经度有显著相关性;渔场重心与暖池指标(暖池重心经度与右边缘经度)的相对位置以及变动趋势在不同气候模式下存在差异,而在同一气候模式中相同。结果表明,渔场重心可通过暖池重心的变化进行预测,而通过构建暖池场与自由鱼群资源丰度的时空分布关系发现,暖池右边缘能够与自由鱼群的空间分布产生联系,为商业性捕捞围网鲣自由鱼群提供渔场边界的指示,为其资源开发与养护提供科学依据。
