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- This is called a deseasonalizing time series. 這叫調和時間數列。
- Time Series Analysis Hamilton J.D. 時間序列分析。
- Predicts the future values for a time series. 預測一個時序的未來值。
- Results A new mode of time series is established. 結果建立了一個新的時間序列模型。
- The kinematic error for ball screws is analyzed by means of Fourier spectrum and time series spectrum analysis. The error sources have been diagnosed. 本文應用Fourier譜分析和時序分析中的譜分析技術,對滾珠絲桿及其副進行了運動誤差分析,診斷出相應的誤差源;
- Tab to display the tree view of the time series model. 選項卡可以顯示時序模型的樹視圖。
- Returns predicted future or historical values for time series data. 返回時序數據的將來或歷史的預測值。
- Time series data set comes with a temporal ordering. 時間序列數據集伴隨著一個時間上的排序。
- This paper studies algebraic modeling of discrete time series. 摘要主要研究離散時間序列上的代數模型。
- An improved method of support vector machine and its applications to financial time series forecasting Estimate of error bounds in the improved support vector regression. 大型工程對工程機械的正常安全運行提出了更高的要求,因此,現代大型工程機械普遍採用了電子監控與故障自診斷系統。
- The method can be used for time series pretreatment and the AR analyzing. 變換方法可用於有限長度時間序列的預處理。
- Simulation of Cunninghamia lanceolata growth by wave-type time series analysis. 杉木生長的起伏型時間序列模擬研究。
- You can define input data for the Microsoft Time Series model in two ways. 可以用兩種方式定義Microsoft時序模型的輸入數據。
- The analyzing tools include SWOT Analysis, Time Series Analysis, etc. 具體用到的分析工具有SWOT分析、時間序列分析方法等等。
- A time series data set is a sequence of random variables indexed by time. 時間序列數據是以時間為指標的一個隨機變數序列。
- The time series was decomposed into several intrinsic mode components (IMCs) via EMD so as to make every component stationary. 首先，針對時間序列的非平穩特徵，通過經驗模式分解將其分解為若干個本徵模式分量，使其中每個分量均成為平穩序列；
- This paper studies the problem of Fractional-Integra tion (FI) time series. 研究了向量分整序列的非線性協整問題。
- For obvious reasons these methodologies can only apply to time series. 因為顯而易見的原因，這些模型只能用於時間序列。
- It must need nonlinear method to reflect essence of the time series veritably. 試想，要真實地反映出這些非線性時間序列的本質，就必須使用非線性工具。
- Through identifies ASF error model by virtue of modern time series analysis theory,the study result shows that the fixed ASF error is basically a stationary stochastic process. Last some useful conclutions are derived by modeling and predict. 對誤差模型進行了系統辨識研究,研究結果表明定點附加二次相位因子(ASF)誤差基本屬於平穩隨機過程。 並運用時間序列分析方法對BPL長波傳播中附加二次相位因子(ASF)進行研究,取得初步模型數據,得到一些有益的結論,為獲得的模型數據為進行ASF誤差的預測及扣除其對長波BPL授時影響,提高授時精度的研究提供了依據。
