This paper models the calculation of the optimal matching speeds of passenger and freight trains with various stage control methods for speed in mixed operations, presents a algorithm for the solution and justifies ...This paper models the calculation of the optimal matching speeds of passenger and freight trains with various stage control methods for speed in mixed operations, presents a algorithm for the solution and justifies it with a practical example.展开更多
This paper addresses the shortcomings of the Sparrow and Eagle Optimization Algorithm (SBOA) in terms of convergence accuracy, convergence speed, and susceptibility to local optima. To this end, an improved Sparrow an...This paper addresses the shortcomings of the Sparrow and Eagle Optimization Algorithm (SBOA) in terms of convergence accuracy, convergence speed, and susceptibility to local optima. To this end, an improved Sparrow and Eagle Optimization Algorithm (HS-SBOA) is proposed. Initially, the algorithm employs Iterative Mapping to generate an initial sparrow and eagle population, enhancing the diversity of the population during the global search phase. Subsequently, an adaptive weighting strategy is introduced during the exploration phase of the algorithm to achieve a balance between exploration and exploitation. Finally, to avoid the algorithm falling into local optima, a Cauchy mutation operation is applied to the current best individual. To validate the performance of the HS-SBOA algorithm, it was applied to the CEC2021 benchmark function set and three practical engineering problems, and compared with other optimization algorithms such as the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA) to test the effectiveness of the improved algorithm. The simulation experimental results show that the HS-SBOA algorithm demonstrates significant advantages in terms of convergence speed and accuracy, thereby validating the effectiveness of its improved strategies.展开更多
针对蚁狮优化算法(Ant Lion Optimization,ALO)后期收敛速度较慢和易陷入局部最优等问题,本文提出基于对数惯性权重的改进蚁狮优化算法(Logarithmic inertia weight based Ant Lion Optimization,LALO)。LALO利用对数函数的特点,实现对...针对蚁狮优化算法(Ant Lion Optimization,ALO)后期收敛速度较慢和易陷入局部最优等问题,本文提出基于对数惯性权重的改进蚁狮优化算法(Logarithmic inertia weight based Ant Lion Optimization,LALO)。LALO利用对数函数的特点,实现对惯性权重的非线性调整,从而更好地平衡算法的全局勘探和局部开采能力。同时,在算法的位置更新中,通过引入对数惯性权重策略来优化蚁狮个体的位置更新过程,降低算法陷入局部收敛的可能性,进而加快收敛速度。本文使用3个经典的测试函数来测试LALO的寻优性能。与已有的群智能算法相比,LALO加快了算法的收敛速度,提高了收敛精度和稳定性。展开更多
As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the bas...As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer（RM） loaded on HY-2 satellite, the sensitivity of some brightness temperature（TB）channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with Wind Sat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.展开更多
文摘This paper models the calculation of the optimal matching speeds of passenger and freight trains with various stage control methods for speed in mixed operations, presents a algorithm for the solution and justifies it with a practical example.
文摘This paper addresses the shortcomings of the Sparrow and Eagle Optimization Algorithm (SBOA) in terms of convergence accuracy, convergence speed, and susceptibility to local optima. To this end, an improved Sparrow and Eagle Optimization Algorithm (HS-SBOA) is proposed. Initially, the algorithm employs Iterative Mapping to generate an initial sparrow and eagle population, enhancing the diversity of the population during the global search phase. Subsequently, an adaptive weighting strategy is introduced during the exploration phase of the algorithm to achieve a balance between exploration and exploitation. Finally, to avoid the algorithm falling into local optima, a Cauchy mutation operation is applied to the current best individual. To validate the performance of the HS-SBOA algorithm, it was applied to the CEC2021 benchmark function set and three practical engineering problems, and compared with other optimization algorithms such as the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA) to test the effectiveness of the improved algorithm. The simulation experimental results show that the HS-SBOA algorithm demonstrates significant advantages in terms of convergence speed and accuracy, thereby validating the effectiveness of its improved strategies.
文摘针对蚁狮优化算法(Ant Lion Optimization,ALO)后期收敛速度较慢和易陷入局部最优等问题,本文提出基于对数惯性权重的改进蚁狮优化算法(Logarithmic inertia weight based Ant Lion Optimization,LALO)。LALO利用对数函数的特点,实现对惯性权重的非线性调整,从而更好地平衡算法的全局勘探和局部开采能力。同时,在算法的位置更新中,通过引入对数惯性权重策略来优化蚁狮个体的位置更新过程,降低算法陷入局部收敛的可能性,进而加快收敛速度。本文使用3个经典的测试函数来测试LALO的寻优性能。与已有的群智能算法相比,LALO加快了算法的收敛速度,提高了收敛精度和稳定性。
基金The National Science Foundation for Young Scientists of China under contract 41306183the National High Technology Research and Development Program(863 Program)of China under contract Nos 2013AA09A505 and 2013AA122803
文摘As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer（RM） loaded on HY-2 satellite, the sensitivity of some brightness temperature（TB）channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with Wind Sat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.
