In order to study the influence factors of acquisition detection target information by lidar and understand the influence degree of each factor, the two-channel phase perturbation model and the two-channel eikonal var...In order to study the influence factors of acquisition detection target information by lidar and understand the influence degree of each factor, the two-channel phase perturbation model and the two-channel eikonal variance model are derived in detail by using the geometrical optics method in this paper, and each factor is discussed in detail. The results show that the transmission distance is the main factor to affect the two-channel perturbation. With the increase of the transmission distance, the disturbing degree will gradually weaken. With the increase of transverse coordinates,the disturbing of two channels will also be weakened. In order to further weaken the disturbing degree, the feature dimension should be far larger than the wavelength, but far less than the transmission distance.展开更多
教-学优化算法是一种新型启发式优化算法。针对教-学优化算法容易陷入局部最优的不足,提出了一种改进教-学优化算法(an improved teaching-learning based optimization,AITLBO)。在教学阶段通过扰动机制提高教师的教学效果,避免算法陷...教-学优化算法是一种新型启发式优化算法。针对教-学优化算法容易陷入局部最优的不足,提出了一种改进教-学优化算法(an improved teaching-learning based optimization,AITLBO)。在教学阶段通过扰动机制提高教师的教学效果,避免算法陷入局部最优。在学习阶段初期分别采取较差学生向优秀学生动态随机学习和优秀学生重新向教师随机学习的策略使当前解向最优方向进化,避免较差解破坏较优解的结构,提高了学习阶段学生的学习效率。在学习阶段后期引入了学生自我反思的学习策略,实现算法对局部信息的精细搜索,提高算法对解空间信息开发的能力,避免了算法因过早收敛易陷入局部最优的不足。将其与目前较优的几种改进TLBO算法和其他启发式优化算法进行性能测试对比,结果表明AITLBO算法具有较高的寻优精度和较快的收敛速度。展开更多
文摘In order to study the influence factors of acquisition detection target information by lidar and understand the influence degree of each factor, the two-channel phase perturbation model and the two-channel eikonal variance model are derived in detail by using the geometrical optics method in this paper, and each factor is discussed in detail. The results show that the transmission distance is the main factor to affect the two-channel perturbation. With the increase of the transmission distance, the disturbing degree will gradually weaken. With the increase of transverse coordinates,the disturbing of two channels will also be weakened. In order to further weaken the disturbing degree, the feature dimension should be far larger than the wavelength, but far less than the transmission distance.
文摘教-学优化算法是一种新型启发式优化算法。针对教-学优化算法容易陷入局部最优的不足,提出了一种改进教-学优化算法(an improved teaching-learning based optimization,AITLBO)。在教学阶段通过扰动机制提高教师的教学效果,避免算法陷入局部最优。在学习阶段初期分别采取较差学生向优秀学生动态随机学习和优秀学生重新向教师随机学习的策略使当前解向最优方向进化,避免较差解破坏较优解的结构,提高了学习阶段学生的学习效率。在学习阶段后期引入了学生自我反思的学习策略,实现算法对局部信息的精细搜索,提高算法对解空间信息开发的能力,避免了算法因过早收敛易陷入局部最优的不足。将其与目前较优的几种改进TLBO算法和其他启发式优化算法进行性能测试对比,结果表明AITLBO算法具有较高的寻优精度和较快的收敛速度。
