1) state transition probablity matrix
状态转移概率矩阵
1.
By means of Bayes formula,state transition probablity matrix of Markov process was revised,and prior probablity distribution was modified into posterior probablity distribution.
采用Bayes方法修订马尔可夫过程的状态转移概率矩阵;将先验概率分布修订为后验概率分布;对整个过程的信息加以吸收,得出能够反映整个过程的状态转移概率矩阵,从而达到预测目的。
2) markov chains / transition probabilities matrix
马尔柯夫链/损伤状态转移概率矩阵
3) possibility transition matrix
概率转移矩阵
1.
The paper constructed a type of possibility transition matrix,based on the theory of Markov process and the result of water quality evaluation,and then endowed the transition possibility with a weight to calculate the degree of absolute advancement.
根据马尔柯夫过程的原理,在水质级别评价结果的基础之上,构造水质变化的概率转移矩阵,并对转移概率赋权计算绝对进步度,然后在此基础上引出相对进步度的概念,用相对进步度来评价河流水质在一段时期内的变化程度。
5) transition probability matrix
转移概率矩阵
1.
Taking a segment of gas pipeline as example, by using the theory of Markov chain, the application of transition probability matrix in prediction for coating degradation with asphalt is illustrated, which provides a basis for determining external anticorrosive coating maintenance cycle.
介绍了埋地燃气管道防腐蚀措施及沥青外防腐蚀层老化状况评价标准,以一燃气管道某管段为实例,通过应用马尔可夫链理论,阐述了利用转移概率矩阵对沥青外防腐蚀层老化状况进行预测的方法,从而为确定外防腐蚀层的合理维修周期提供了理论依据。
2.
For the difficulty of getting transition probability matrixes in various directions in Markov chain(models),the paper presents a method to figure out it,which makes getting transition probability matrixes of (different) neighborhood systems of Markov chain models easier and more feasible.
针对在油气储层随机模拟中马尔可夫链模型的不同方向的转移概率矩阵求取困难的问题,提出一种二维剖面中不同方向的转移概率矩阵求取方法,这种方法的提出使得不同阶次的各向同性和各向异性的邻域系统的转移概率矩阵的求取变得容易可行。
3.
It is necessary to extend 1D Markov chain model into 2D or 3D model and give the effective solutions for estimating the transition probability matrix and initializing border status.
在应用该模型时,须将一维的Markov链模型拓展到二维、三维,同时要对侧向转移概率矩阵的估算和顶层初始化这2个关键问题给出有效的解决方案。
6) Markov probability transfer matrix
Markov概率转移矩阵
补充资料：转移概率矩阵
转移概率矩阵
matrix of transition probabilities
转移概率矩阵【“.枕议of七队d位翻声如城翻;nepex-。江皿‘区.ePo，.oeTe曲Ma邓H”a】 状态集S至多为可数的齐次MaP劝.链(Mark0Vd.in)奴O在时刻:的转移概率(加璐币皿probab正-公)构成的矩阵尸:=!}Pi)(O”，其中 夕。(t)=p{看(t)=jl亡(0)=i}，i，j“5.离散时间Ma匹oB链或连续时间正则MaPx伪链的转移概率矩阵i}儿(t)“对任意t>0和i，j“S满足以下条件: p。(‘))”，属p‘，(‘)一‘，即它们是随机矩阵(sto比出tic Inatr认)，而对非正则链则有 ，。(亡))0，艺夕。(t)‘l， 夕‘S称这种矩阵为次随机的(sub·stoc】秘tic). 由于齐次Ma琳oB链的基本(CllaP~一K~。ro-poB)性质 ，。(“+‘)一蕙，‘*(“)，*，(亡)，矩阵族{尸‘:亡)0}形成一个乘法半群(m川tiplicativeseITU一gro叩);如果时间是离散的，这个半群由尸:唯一决定.A，M.3y6KoB撰
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条