Single unmanned aerial vehicle(UAV)multitasking plays an important role in multiple UAVs cooperative control,which is as well as the most complicated and hardest part.This paper establishes a threedimensional topograp...Single unmanned aerial vehicle(UAV)multitasking plays an important role in multiple UAVs cooperative control,which is as well as the most complicated and hardest part.This paper establishes a threedimensional topographical map,and an improved adaptive differential evolution(IADE)algorithm is proposed for single UAV multitasking.As an optimized problem,the efficiency of using standard differential evolution to obtain the global optimal solution is very low to avoid this problem.Therefore,the algorithm adopts the mutation factor and crossover factor into dynamic adaptive functions,which makes the crossover factor and variation factor can be adjusted with the number of population iteration and individual fitness value,letting the algorithm exploration and development more reasonable.The experimental results implicate that the IADE algorithm has better performance,higher convergence and efficiency to solve the multitasking problem compared with other algorithms.展开更多
为进一步提高分割精度并加快分割速度,提出了一种基于邻域搜索可选外部存档自适应差分进行算法(简称为JADE-GL)的二维Otsu多阈值图像分割方案。首先,针对原始JADE算法精英突变策略收敛速度慢、容易陷入局部最优等问题,提出了基于邻域半...为进一步提高分割精度并加快分割速度,提出了一种基于邻域搜索可选外部存档自适应差分进行算法(简称为JADE-GL)的二维Otsu多阈值图像分割方案。首先,针对原始JADE算法精英突变策略收敛速度慢、容易陷入局部最优等问题,提出了基于邻域半径搜索的改进突变策略,以提升算法的全局探索和开发能力。然后,将所提算法与现有分割方法以及其他JADE变种算法进行二维Otsu多阈值分割对比实验。最后,通过函数收敛曲线、分割距离测度、峰值信噪比(peak signal to noise ratio,PSNR)等指标定量分析算法的性能。实验结果表明,随着阈值数增加,提出的算法无论在收敛速度、分割精度还是分割图像效果上都有显著提升。展开更多
文摘Single unmanned aerial vehicle(UAV)multitasking plays an important role in multiple UAVs cooperative control,which is as well as the most complicated and hardest part.This paper establishes a threedimensional topographical map,and an improved adaptive differential evolution(IADE)algorithm is proposed for single UAV multitasking.As an optimized problem,the efficiency of using standard differential evolution to obtain the global optimal solution is very low to avoid this problem.Therefore,the algorithm adopts the mutation factor and crossover factor into dynamic adaptive functions,which makes the crossover factor and variation factor can be adjusted with the number of population iteration and individual fitness value,letting the algorithm exploration and development more reasonable.The experimental results implicate that the IADE algorithm has better performance,higher convergence and efficiency to solve the multitasking problem compared with other algorithms.
文摘采用自主水下航行器(Autonomous Underwater Vehicle,AUV)磁测平台可开展海洋地磁场测量、水下磁性目标探测和识别等工作,AUV磁测平台具有广阔的应用前景,但目前AUV载体磁干扰补偿技术研究尚不成熟,制约着水下航行器测磁精度。基于磁测平台抗磁干扰基本原理,提出一种基于线性种群规模缩减和成功历史的参数自适应差分进化(Success History-based Adaptive Differential Evolution with Linear Population Size Reduction,L-SHADE)算法的AUV载体磁干扰参数辨识的数值模拟方法。用磁偶极子和旋转椭球壳混合模型来等效模拟AUV载体磁干扰,通过模拟航行获得多组磁测数据,据此建立磁干扰参数辨识模型,并采用L-SHADE算法求解。通过数值模拟实验定量分析研究磁测平台测磁精度随磁传感器、平台姿态及航向等误差的传播规律。研究结果表明:当磁传感器测量精度为10 nT、姿态测量精度为0.01°、航向测量精度为0.1°时,测磁误差可小于100 nT。设计的AUV磁测平台抗干扰试验表明,地磁场总量最大相对误差为1.07%。
文摘为进一步提高分割精度并加快分割速度,提出了一种基于邻域搜索可选外部存档自适应差分进行算法(简称为JADE-GL)的二维Otsu多阈值图像分割方案。首先,针对原始JADE算法精英突变策略收敛速度慢、容易陷入局部最优等问题,提出了基于邻域半径搜索的改进突变策略,以提升算法的全局探索和开发能力。然后,将所提算法与现有分割方法以及其他JADE变种算法进行二维Otsu多阈值分割对比实验。最后,通过函数收敛曲线、分割距离测度、峰值信噪比(peak signal to noise ratio,PSNR)等指标定量分析算法的性能。实验结果表明,随着阈值数增加,提出的算法无论在收敛速度、分割精度还是分割图像效果上都有显著提升。
