vector markov process 中文意思是什麼
vector markov process
解釋
向量馬爾可夫過程-
A dynamic input - output model with random consumption vector s ( t, ), random consumption coefficient matrix and random investment coefficient matrix which the time lag is one has been discussed. by means of modern stochastic analysis and markov process, it has been proved that the random dynamic input - output model does not have a balanced growth solution
對具有隨機消費向量s （ t ， ） ，隨機投入產出消耗系數矩陣、隨機投資系數矩陣的動態模型，利用現代概率分析、馬氏過程等工具，證明了其經濟穩定增長解不存在的結論 -
The class of systems is a hybrid class of systems with two components in the vector state. the first component refers to the mode and the second one to the state. the mode is described by a continuous markov process with finite state space
這類系統是一類混合系統，由兩部分構成，第一部分是系統的模式，第二部分是系統的狀態，模式可以用連續時間離散狀態的markov過程來描述，在每一個模式中，狀態可由一個隨機微分方程表示。 -
Chapter2 : traditional time series models and multivariate fuzzy time series models. the chapter introduces the vector arma model, transfer arima model, seasonal arima, and arima model of traditional time series models, and two - factors models, heuristic models, and markov models of multivariate fuzzy time series models. i devise the process of the model construction, and propose the findings
本章介紹傳統時間數列模型（向量arma模型、 arima轉移函數模型、季節性arima模型以及arima模型）與多變量模糊時間數列三種模型?二因子模型（ two - factormodels ） 、引導式模型（ heuristicmodels ） 、馬可夫模型（ markovmodels ） ，模型建構步驟與流程，及傳統時間數列模型轉換為多變量模糊時間數列模型過程，並分別針對多變量模糊時間數列三種模型提出本研究不同於先前研究之處。
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