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    • 20. 发明授权
    • Method and system for utilizing Markov chain Monte Carlo simulations
    • 利用马尔科夫链蒙特卡洛模拟的方法和系统
    • US09009095B1
    • 2015-04-14
    • US13005433
    • 2011-01-12
    • Mohsin Saleet FafriTuan Minh Hoang-TrongGeorge Stuart Blair Williams
    • Mohsin Saleet FafriTuan Minh Hoang-TrongGeorge Stuart Blair Williams
    • G06N7/06G06F9/44G06N7/00G06F19/00
    • G06N7/005G06F17/18
    • Systems and methods for determining a probability of changing from one state to another in a stochastic entity, comprising: determining the compact component matrix utilizing characteristic information of the stochastic entity; determining the compact composite component matrix by taking a Kroneker product of the compact component matrix and an identity matrix; determining and placing all current states for the stochastic entity into a state space matrix; determining a Q matrix and/or a transition rate matrix using the compact composite component matrix and basic conditions or variables of the problem domain and/or a compact transition rate matrix; and performing Markov chain Monte Carlo (MCMC) simulation using information from the state space matrix and information from the transition rate matrix to determine the probability of changing from one state to another state in the stochastic entity.
    • 用于确定在随机实体中从一个状态变化到另一个状态的概率的系统和方法,包括:利用所述随机实体的特征信息确定所述紧凑分量矩阵; 通过采用紧凑分量矩阵的Kroneker积和单位矩阵来确定紧凑复合成分矩阵; 确定并将随机实体的所有当前状态置于状态空间矩阵中; 使用紧凑复合分量矩阵和问题域的基本条件或变量和/或紧凑转换速率矩阵来确定Q矩阵和/或转换速率矩阵; 并使用来自状态空间矩阵的信息和来自转换速率矩阵的信息来执行马尔可夫链蒙特卡洛(MCMC)模拟,以确定随机实体中从一种状态变为另一种状态的概率。