For the Sylvester continued fraction expansions of real numbers,FAN et al.(2007)proved that,for almost all real numbers,the nth partial quotient grows exponentially with respect to the product of the first n-1 partial...For the Sylvester continued fraction expansions of real numbers,FAN et al.(2007)proved that,for almost all real numbers,the nth partial quotient grows exponentially with respect to the product of the first n-1 partial quotients.In this paper,we establish the Hausdorff dimension of the exceptional set where the growth rate is a general function.展开更多
针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,...针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,从而更好地平衡算法的全局搜索能力和局部搜索能力;同时,在算法的位置更新公式中引入S型函数,并利用个体粒子自身的适应度值与群体平均适应度值的比值自适应地调整搜索步长,从而提高算法的搜索效率。在若干经典测试函数上的仿真实验结果表明,与已有的几种改进粒子群算法相比,SAPSO在收敛速度和求解精度方面均有较大优势。展开更多
基金Supported by Projects from Chongqing Municipal Science and Technology Commission(CSTB2022NSCQ-MSX0445)。
文摘For the Sylvester continued fraction expansions of real numbers,FAN et al.(2007)proved that,for almost all real numbers,the nth partial quotient grows exponentially with respect to the product of the first n-1 partial quotients.In this paper,we establish the Hausdorff dimension of the exceptional set where the growth rate is a general function.
文摘针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,从而更好地平衡算法的全局搜索能力和局部搜索能力;同时,在算法的位置更新公式中引入S型函数,并利用个体粒子自身的适应度值与群体平均适应度值的比值自适应地调整搜索步长,从而提高算法的搜索效率。在若干经典测试函数上的仿真实验结果表明,与已有的几种改进粒子群算法相比,SAPSO在收敛速度和求解精度方面均有较大优势。
