对马尔可夫可修系统新类型故障发生时间的分布问题进行研究。
The time distribution of the ith new type failure for Markov repairable systems was studied.
本文对BMS进行了介绍，并分别利用随机过程中马尔可夫链的知识和时间序列中的INAR(1)模型对BMS进行了研究。
This paper will first introduce BMS, then study BMS by Markov chain in stochastic process and INAR (1) model in time series.
利用在更换周期点上具有的马尔可夫性质，以系统首次故障前平均工作时间最大为目标建立了确定最佳更换周期的模型。
Using the property of Markov at the points of replacement period, a model of determining the optimal period is developed with objective of maximizing the mean time to first failure of system.
并在寿命、修理延迟和维修时间均服从指数分布的情况下，用马尔可夫更新过程理论导出了系统的可用度。
When the distribution of life, delayed repair and imperfect repair time are all exponential, Markov renewal process for educing the availability is presented.
利用齐次离散时间马尔可夫链模型描述了大地震沿一条活动断裂带的迁移过程。
A homogeneous discrete-time Markov chains model is used to characterize migration of large earthquakes along an active fault zone.
文摘：利用马尔可夫过程给出了串联可修系统各状态的不可用度表达式及平均修复时间表达式。
Abstract: In this paper, Formula of MTTR( meam time to repair) and unavailability of every states for series repairable system are given using Markov processes.
然而现有的分段半马尔可夫模型只能解决具有近似相同长度的模式检测问题，不允许模式在时间上存在缩放。
However, the existing segmental semi-Markov model can only detect the matching sequences with approximately equal length to that of the query pattern, i. e., without time scaling.
马尔可夫切换模型是一种研究时间序列结构性变化的方法。
Markov-switching model is a method applied to investigating the structural changes of time series.
由于在语音识别中被广泛应用的隐马尔可夫模型(HMM)是一重马尔可夫模型，它不能充分地描述语音信号的时间相依性。
Since the widely used Hidden Markov model (HMM) in speech recognition is first order Markov model, it can not fully model the temporal dependence of speech signal.
针对知识库结构，通过专家系统的推理时间研究了实时性问题，利用时间齐次马尔可夫链为专家系统知识库进行建模，并给出了相应的时间估计模型及其排列准则。
This paper takes the knowledge-base architecture as an example to study the corresponding problem of the alignment. At last, Temporally homogeneous Markov chain is used to modeling...
方法二针对状态空间巨大的情况，先以一定的标准对状态空间进行截尾，再应用马尔可夫模型获得系统的稳态可用度、首次故障前平均时间、稳态故障频度等可靠性指标。
The other first truncates the state space according to some criterion in view of the explosive number of states. Markov model is introduced to obtain some important reliability indexes.
方法二针对状态空间巨大的情况，先以一定的标准对状态空间进行截尾，再应用马尔可夫模型获得系统的稳态可用度、首次故障前平均时间、稳态故障频度等可靠性指标。
The other first truncates the state space according to some criterion in view of the explosive number of states. Markov model is introduced to obtain some important reliability indexes.
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