To enhance the generalization performance of radial basis function （RBF） neural networks, an RBF neural network based on a q-Gaussian function is proposed. A q-Gaussian function is chosen as the radial basis functio...To enhance the generalization performance of radial basis function （RBF） neural networks, an RBF neural network based on a q-Gaussian function is proposed. A q-Gaussian function is chosen as the radial basis function of the RBF neural network, and a particle swarm optimization algorithm is employed to select the parameters of the network. The non-extensive entropic index q is encoded in the particle and adjusted adaptively in the evolutionary process of population. Simulation results of the function approximation indicate that an RBF neural network based on q-Gaussian function achieves the best generalization performance.展开更多
Rock failure can cause serious geological disasters,and the non-extensive statistical features of electric potential(EP)are expected to provide valuable information for disaster prediction.In this paper,the uniaxial c...Rock failure can cause serious geological disasters,and the non-extensive statistical features of electric potential(EP)are expected to provide valuable information for disaster prediction.In this paper,the uniaxial compression experiments with EP monitoring were carried out on fine sandstone,marble and granite samples under four displacement rates.The Tsallis entropy q value of EPs is used to analyze the selforganization evolution of rock failure.Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes.A self-organized critical prediction method with q value is proposed.The results show that the probability density function(PDF)of EPs follows the q-Gaussian distribution.The displacement rate is positively correlated with q value.With the displacement rate increasing,the fracture mode changes,the damage degree intensifies,and the microcrack network becomes denser.The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode.The q value of EPs can be used as an effective prediction index for rock failure like b value of acoustic emission(AE).The results provide useful reference and method for the monitoring and early warning of geological disasters.展开更多
利用 T 矩阵法研究光镊中微粒大小与入射光束波长相近时，光镊捕获效率与入射光束的阶数、微粒的折射率和尺寸大小的关系．对拉盖尔-高斯光束光镊和高斯光束光镊的轴向和横向捕获效率进行比较．计算结果表明：不同阶数的拉盖尔-高斯光...利用 T 矩阵法研究光镊中微粒大小与入射光束波长相近时，光镊捕获效率与入射光束的阶数、微粒的折射率和尺寸大小的关系．对拉盖尔-高斯光束光镊和高斯光束光镊的轴向和横向捕获效率进行比较．计算结果表明：不同阶数的拉盖尔-高斯光束对微粒捕获效率的影响不同，阶数不超过4的拉盖尔-高斯光束的捕获效率高；微粒半径增加时，拉盖尔-高斯光束的轴向捕获效率逐渐增大，且捕获域也增加，高斯光束的最大捕获效率基本保持不变但捕获域逐渐增大；微粒折射率增加时，拉盖尔-高斯光束和高斯光束的轴向和横向捕获效率均先增加后递减，捕获效率出现了一个峰值，微粒折射率约在1．39～1．69是稳定捕获的最佳数值．展开更多
文摘To enhance the generalization performance of radial basis function （RBF） neural networks, an RBF neural network based on a q-Gaussian function is proposed. A q-Gaussian function is chosen as the radial basis function of the RBF neural network, and a particle swarm optimization algorithm is employed to select the parameters of the network. The non-extensive entropic index q is encoded in the particle and adjusted adaptively in the evolutionary process of population. Simulation results of the function approximation indicate that an RBF neural network based on q-Gaussian function achieves the best generalization performance.
基金supported by National Key R&D Program of China(2022YFC3004705)the National Natural Science Foundation of China(Nos.52074280,52227901 and 52204249)+1 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX24_2913)the Graduate Innovation Program of China University of Mining and Technology(No.2024WLKXJ139).
文摘Rock failure can cause serious geological disasters,and the non-extensive statistical features of electric potential(EP)are expected to provide valuable information for disaster prediction.In this paper,the uniaxial compression experiments with EP monitoring were carried out on fine sandstone,marble and granite samples under four displacement rates.The Tsallis entropy q value of EPs is used to analyze the selforganization evolution of rock failure.Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes.A self-organized critical prediction method with q value is proposed.The results show that the probability density function(PDF)of EPs follows the q-Gaussian distribution.The displacement rate is positively correlated with q value.With the displacement rate increasing,the fracture mode changes,the damage degree intensifies,and the microcrack network becomes denser.The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode.The q value of EPs can be used as an effective prediction index for rock failure like b value of acoustic emission(AE).The results provide useful reference and method for the monitoring and early warning of geological disasters.
文摘利用 T 矩阵法研究光镊中微粒大小与入射光束波长相近时，光镊捕获效率与入射光束的阶数、微粒的折射率和尺寸大小的关系．对拉盖尔-高斯光束光镊和高斯光束光镊的轴向和横向捕获效率进行比较．计算结果表明：不同阶数的拉盖尔-高斯光束对微粒捕获效率的影响不同，阶数不超过4的拉盖尔-高斯光束的捕获效率高；微粒半径增加时，拉盖尔-高斯光束的轴向捕获效率逐渐增大，且捕获域也增加，高斯光束的最大捕获效率基本保持不变但捕获域逐渐增大；微粒折射率增加时，拉盖尔-高斯光束和高斯光束的轴向和横向捕获效率均先增加后递减，捕获效率出现了一个峰值，微粒折射率约在1．39～1．69是稳定捕获的最佳数值．
