The concepts of Markov process in random environment, q-matrix in random environment, and q-process in random environment are introduced. The minimal q-process in random environment is constructed and the necessary an...The concepts of Markov process in random environment, q-matrix in random environment, and q-process in random environment are introduced. The minimal q-process in random environment is constructed and the necessary and sufficient conditions for the uniqueness of q-process in random environment are given.展开更多
This article is a continuation of[9].Based on the discussion of random Kolmogorov forward（backward）equations,for any given q-matrix in random environment, Q（θ）=（q（θ;x,y）,x,y∈X）,an infinite class of q-proces...This article is a continuation of[9].Based on the discussion of random Kolmogorov forward（backward）equations,for any given q-matrix in random environment, Q（θ）=（q（θ;x,y）,x,y∈X）,an infinite class of q-processes in random environments satisfying the random Kolmogorov forward（backward）equation is constructed.Moreover, under some conditions,all the q-processes in random environments satisfying the random Kolmogorov forward（backward）equation are constructed.展开更多
This paper introduces some concepts such as q- process in random environment, Laplace transformation, ergodic potential kernel, error function and some basic lemmas.We study the continuity and Laplace transformation o...This paper introduces some concepts such as q- process in random environment, Laplace transformation, ergodic potential kernel, error function and some basic lemmas.We study the continuity and Laplace transformation of random transition function. Finally, we give the sufficient condition for the existence of ergodic potential kernel for homogeneous q- processes in random environments.展开更多
Based upon the composition of C-Si-Mn,four types of transformation induced plasticity（ TRIP） steels with different contents of Si and M n were designed,which are subjected to quenching and partitioning（ Q＆P）proce...Based upon the composition of C-Si-Mn,four types of transformation induced plasticity（ TRIP） steels with different contents of Si and M n were designed,which are subjected to quenching and partitioning（ Q＆P）processes with variable austenitizing temperatures. The as-treated steels exhibits good combination of high strength and substantial elongation. In particular,with austenitizing at 820 ℃,0. 18C-1. 8Si-2. 2M n（ %） steel and0. 18C-1. 8Si-2. 5M n（ %） steel possessed high elongation（ more than 20%） with the tensile strength over 1000 M Pa. The microstructures of the as-treated steels were obtained by scanning electron microscope,the volume fraction and carbon content of retained austenite has been quantified by X-ray diffraction. The designed Q＆P processed steels contained a multiphase microstructure including ferrite,lath martensite,and retained austenite. The volume fraction and carbon content of those steels were higher,which was treated by Q＆P processes with austenitizing at 820 ℃. Due to the TRIP effect during the deformation process,retained austenite gives better stability as well as effectively improves the formability of steels with slightly decreasing the strength,contributing to overall better performance.展开更多
电力传感网可以用于对电力网络的设备工作状态和工作环境等信息实时采集和获取,对于电力网络设施的实时监控与快速响应具有重要作用。针对系统在数据排队时延和丢包率上的特殊要求,提出了一种基于强化学习的电力传感网资源分配方案。在...电力传感网可以用于对电力网络的设备工作状态和工作环境等信息实时采集和获取,对于电力网络设施的实时监控与快速响应具有重要作用。针对系统在数据排队时延和丢包率上的特殊要求,提出了一种基于强化学习的电力传感网资源分配方案。在资源受限的情况下,通过资源分配算法来优化传感器节点的排队时延和丢包率,并将该优化问题建模为马尔可夫决策过程(Markov decision process,MDP),通过双深度Q网络(double deep Q-learning,DDQN)来对优化目标函数求解。仿真结果与数值分析表明,所提方案在收敛性、排队时延和丢包率等方面的性能均优于基准方案。展开更多
文摘The concepts of Markov process in random environment, q-matrix in random environment, and q-process in random environment are introduced. The minimal q-process in random environment is constructed and the necessary and sufficient conditions for the uniqueness of q-process in random environment are given.
基金the NNSF of China(10371092,10771185,10471148)the Foundation of Wuhan University
文摘This article is a continuation of[9].Based on the discussion of random Kolmogorov forward（backward）equations,for any given q-matrix in random environment, Q（θ）=（q（θ;x,y）,x,y∈X）,an infinite class of q-processes in random environments satisfying the random Kolmogorov forward（backward）equation is constructed.Moreover, under some conditions,all the q-processes in random environments satisfying the random Kolmogorov forward（backward）equation are constructed.
基金Supported by the National Natural Science Foundation of China (10371092)
文摘This paper introduces some concepts such as q- process in random environment, Laplace transformation, ergodic potential kernel, error function and some basic lemmas.We study the continuity and Laplace transformation of random transition function. Finally, we give the sufficient condition for the existence of ergodic potential kernel for homogeneous q- processes in random environments.
文摘Based upon the composition of C-Si-Mn,four types of transformation induced plasticity（ TRIP） steels with different contents of Si and M n were designed,which are subjected to quenching and partitioning（ Q＆P）processes with variable austenitizing temperatures. The as-treated steels exhibits good combination of high strength and substantial elongation. In particular,with austenitizing at 820 ℃,0. 18C-1. 8Si-2. 2M n（ %） steel and0. 18C-1. 8Si-2. 5M n（ %） steel possessed high elongation（ more than 20%） with the tensile strength over 1000 M Pa. The microstructures of the as-treated steels were obtained by scanning electron microscope,the volume fraction and carbon content of retained austenite has been quantified by X-ray diffraction. The designed Q＆P processed steels contained a multiphase microstructure including ferrite,lath martensite,and retained austenite. The volume fraction and carbon content of those steels were higher,which was treated by Q＆P processes with austenitizing at 820 ℃. Due to the TRIP effect during the deformation process,retained austenite gives better stability as well as effectively improves the formability of steels with slightly decreasing the strength,contributing to overall better performance.
基金Project(52001281)supported by the National Natural Science Foundation of ChinaProject(192102210012)supported by Key Scientific and Technological Research Projects in Henan Province,ChinaProject(202300410431)supported by Natural Science Foundation of Henan Province,China。
文摘电力传感网可以用于对电力网络的设备工作状态和工作环境等信息实时采集和获取,对于电力网络设施的实时监控与快速响应具有重要作用。针对系统在数据排队时延和丢包率上的特殊要求,提出了一种基于强化学习的电力传感网资源分配方案。在资源受限的情况下,通过资源分配算法来优化传感器节点的排队时延和丢包率,并将该优化问题建模为马尔可夫决策过程(Markov decision process,MDP),通过双深度Q网络(double deep Q-learning,DDQN)来对优化目标函数求解。仿真结果与数值分析表明,所提方案在收敛性、排队时延和丢包率等方面的性能均优于基准方案。
