time series vector 中文意思是什麼
time series vector
解釋
時序向量-
Integrating kernel principal component analysis with least squares support vector machines for time series forecasting problems
基於核主成分分析與最小二乘支持向量機結合處理時間序列預測問題 -
What the practical problems is often gotten is a single variable time series which has a time interval of t, reflect by a lot of interactive physics factor, containing the mark of all variates participating in movement, traditional time series analysis is to analyse going from this array to the form directly it ' s time develops, one dimension analysis loses useful information, the characteristics of phase space reconstruction method is to construct one dimension scalar quantity to high dimension vector, prop the geometry space of the state, show all dynamical information of system in phase space. the characteristic that just constructs again according to the phase space in this text, analyse the time series of responding, use the relevant knowledge of symbol dynamics and reconstruct phase space, put forward a kind of relation degree analysis method of the systematic mathematics model which has theory basis, so reach the correction of calculation mathematics model, make it accord with the actual systematic state
實際問題中常常得到的是一個時間間隔為t的單變量的時間序列，它是許多物理因子相互作用的綜合反映，蘊藏著參與運動的全部變量的痕跡，傳統的時序分析是直接從這個序列去形式地分析它的時間演變，一維分析必然喪失許多有用信息，相空間重構方法的特點是把一維標量數據構造成高維矢量，支起狀態的幾何空間，在相空間中展示系統全部動力信息。本文正是根據相空間重構的特點，對響應時間序列進行分析，利用符號動力學、重構相空間等方法，提出一種有理論依據的系統數學模型關聯度分析方法，從而達到修正計算數學模型，使其更符合實際系統狀態的目的。 -
In fact, vector spectrum comprises a " series of analysis methods : fundamental vector spectrum, vector power spectrum, vector spectrum that used to analysis stationary signals, and short time vector spectrum to non - stationary signals
矢譜分析是針對旋轉機械矢量信號的一系列分析方法的總稱。矢譜范疇包括針對平穩信號的矢量譜、矢功率譜、矢量倒譜以及針對非平穩信號的短時矢譜等眾多分析方法。 -
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。 -
Chaotic time series forecasting using online least squares support vector machine regression
基於在線最小二乘支持向量機回歸的混沌時間序列預測
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