時式序列 的英文怎麼說

中文拼音 [shíshìxùliè]
時式序列 英文
sequence of tense
  • 時 : shí］Ⅰ名1 （比較長的一段時間）time; times; days:當時at that time; in those days; 古時 ancient tim...
  • 式 : 名詞1 （樣式） type; style 2 （格式） pattern; form 3 （儀式; 典禮） ceremony; ritual 4 （自然科...
  • 列 : Ⅰ動1 （排列） arrange; form a line; line up 2 （安排到某類事物之中） list; enter in a list Ⅱ名詞1...
  1. We ca n ' t divide the multiple streams time series into singleness times series simply in the research of multiple streams time series, we ' ll dissever the relation between the events of the multiple streams. although the msdd can find the dependency relationship of multiple streams, but it have n ' t the initialization of the events, the express of the time relationship between events is not frank, the cost of the algorithm is expensive ( o ( n5 ) ), i ca n ' t find much more knowledge in multiple time series, it find the dependency patterns only of the multiple time series, so there need a new more effective, frank, complete algorithm to find the knowledge

    研究多流時序不能簡單地將它割裂為單流時序，因為這樣就割裂了數據流事件之間的關系。雖然msdd能夠發現多流時間序列中的依賴模式，但是由於其缺少對數據的初始化、事件之間時間關系的表示不直觀、演算法執行的時間空間開銷很大（ o （ n ~ 5 ） ） 、不能夠充分發現多流時間序列包含的知識，它只發現依賴關系，因此研究新的，高效，全面的發現多流時間序列事件之間關系的演算法成為必要。本文分析了單一和多流時間序列中的知識發現，把多流時間序列事件內部存在的關系表示為：關聯模式、依賴模式、突變模式。
  2. Ptwma is an effective successful algorithm and model to the knowledge discovery of the multiple streams time series

    Ptwma為分散式，并行控掘多流時間序列提供了一種有效的演算法和模型。
  3. 4. research of online similar search in a streaming time series an algorithm on online similar search in a streaming time series is proposed

    4 ）動態時間序列在線模式的相似性查找研究針對時間序列實時分析的需要，給出了一種動態序列的在線相似性查找演算法。
  4. These researches will help us to discover changing or developing principle of things, support to decision - making, etc. the thesis addresses several key technical problems of pattern mining and its search based similarity in time series, which covers feature patterns and relationship patterns mining, pattern search based similarity in time series and stream time series and issues concerning application system implementation oriented to analysis. major contributions of this thesis include : 1. research of mining feature patterns in time series a novel method is proposed to discovery frequent pattern from time series

    本文在分析時間序列特點和實際應用需求的基礎上，針對時間序列的挖掘與相似性查找一些關鍵技術進行了研究，具體包括特徵模式挖掘、多序列關聯模式挖掘、相似性模式查找等方面，所做的工作和取得的創新成果體現在以下三個方面： 1 ）時間序列特徵模式挖掘研究首次提出了一種基於互關聯后繼樹模型的時序特徵模式挖掘方法。
  5. This paper analysis the data mining of the single nd multiple streams time series, and draw a conclusion that the relationship between the events of the multiple streams time series are the association patterns dependency patterns, sudden patterns, this paper call them are structure patterns, the existing algorithm have n ' t discuss these patterns, although msdd discussed the dependency patterns, however, it ignored the association patterns, sudden patterns, this paper have a definition of the association patterns, sudden patterns and dependency patterns, and have a complete, frank algorithm called twma ( time window moving and filtering algorithm ), the peculiarity of this algorithm is that events is listed by the time window, by this way, the relationship of the events is clear

    本文將它們統稱為結構模式，而這正是目前其它演算法、沒有考慮到的，雖然msdd考慮了事件之間的依賴關系，但它忽略了突變模式，關聯模式等重要的知識表示。本文給出了關聯模式、依賴模式、突變模式的定義，提出了一個比較靈活全面、直觀的挖掘它們的演算法：時間窗口移動篩選演算法twma （ timewindowmovingandfilteringalgorithm ） 。該演算法的一個突出特點是將時間序列事件按時間窗口序列化，使得事件之間的時間關系表示很直觀，該演算法能成功地從多流時間序列中發現了事件之間的關系。
  6. These researches will help us to discover changing or developing principle of things, support to decision - making, etc. the thesis addresses several key technical problems of pattern mining and its search based similarity in time series, which covers feature patterns and relationship patterns mining, pattern search based on similarity in time series and stream time series and issues concerning application system implementation oriented to analysis. major contributions of this thesis include : 1. research of mining feature patterns in time series a novel method is proposed to discovery frequent pattern from time series

    本文在分析時間序列特點和實際應用需求的基礎上，針對時間序列的挖掘與相似性查找一些關鍵技術進行了研究，具體包括特徵模式挖掘、多序列關聯模式挖掘、相似性模式查找，在線相似性查找以及最終的分析應用系統開發等方面，所做的工作和取得的創新成果體現在以下五個方面： 1 ）時間序列特徵模式挖掘研究首次提出了一種基於互關聯后繼樹模型的時序特徵模式挖掘方法。
  7. We can find a polynomial model of a time series in case its associated matrix is not diagonal and not of full rank by using the transformations of the exponential and the logarithm

    對于不能對角和不滿秩的時間序列矩陣，運用指數對數的可逆變換及相關的列變換化為滿秩可對角的時間序列矩陣，從而找到代數多項式模型。
  8. In this article, firstly the background of the textile trade conflicts within sino - us or sino - euro are introduced, thus learn that how to discern and dodge the foreign trade risks, how to choose the appropriate investment projects have already become one of the most important questions for exporting companies on foreign trade affairs well - known as high investment and high risk. so the main text makes a risk analysis qualitatively and quantitatively on a textile - exporting trading company from three angles of statistic 、 game theory and portfolio theory, which is the main content that we studied. firstly, the statistic article adopts data of the transaction closing price of the textile clothing index in shenzhen stock exchange at the end of each quarter as well as several other kinds of data reflecting the macro - economic changes, performs an empirical analysis of these data according to the theory of co - integration test 、 granger cause test and impulse response function of time series in economitric, and learn that the impact to ti is more obvious by the economic index reflecting local commodity price level and economic prosperity degree home and abroad, as well as the impact degree and the time lag degree, and knows the macro - economic risks faced by textile business enterprises ; after that by the game theory angle we analyze exactly the managing risks faced by one textile export corporation named beauty. from the game expansion chart the system arrangement between censor ways by exportation goal countries and exporting strategies by the exporting enterprises has been analyzed. involving the benefit assignment between them both the limited rounds and infinite rounds negotiations of cooperation games have been studied, and then country responsibility and the enterprise managing risks on foreign trade affairs and so on have been analyzed exactly ; in order to realize the investment multiplication in the certain degree to disperse the risk, the

    本文首先介紹了中美、中歐紡織品貿易爭端的來龍去脈，由此可知在涉外貿易這種以高投入、高風險著稱的行業里，如何甄別和規避外貿風險、如何選擇合適的投資項目已經成為外貿企業的首要問題。因此，正文分別從統計學、博弈論和投資組合三種角度對涉外紡織品貿易公司風險進行了定性和定量的分析，這也是本文的主要研究內容。首先，統計學篇選取了深圳證券交易所行業分類指數?紡織服裝指數（ ti ）每一季度末的交易收盤價和若干種反映宏觀經濟變化的指標，利用計量經濟學中時間序列的協整檢驗、 granger因果檢驗和脈沖反應函數等理論做實證分析，從而得知反映國內物價水平和國內外經濟景氣程度的經濟指標對紡織板塊上市值的沖擊比較明顯，且可知沖擊程度和時滯度，進而分析出涉外紡織企業所面臨的宏觀經濟風險;接著，從博弈論的角度具體分析一家紡織品出口公司（ beauty ）的外貿活動所面臨的各種經營風險，該篇從博弈擴展圖入手，分析了出口目的國審查方式與本企業出口策略之間的制度安排;並圍繞雙方的利益分配，研究了有限回合和無限回合合作談判博弈，然後具體論述了國家責任和企業涉外經營風險等問題;在一定程度上為了實現投資多元化來分散風險的目的，投資組合篇從經典的markowitz模型著手，在一些特定條件的限制下，給出了一個相應的投資組合模型。
  9. It also analyzes the history and the present situation of the shift in village in this part. in the fourth part, i establish employment elastic time series model to analyze the ability of absorbing labor. finally, some supporting stratagems are proposed to promote village surplus labor shift, to adjusts the employment structure and to optimize the industrial structure

    第三部分用特化系數考察江蘇各區域的勞動力分佈情況，並分析了江蘇農村剩餘勞動力轉移的歷史和現狀，以及存在的問題;第四部分建立就業彈性的時間序列模型，對非農產業的勞動力吸納能力進行定量分析，並對非農產業內部具體產業的勞動力吸納能力作了比較;最後，把區域空間結構發展模式與江蘇經濟發展的具體特徵融合到一起，提出轉移江蘇農村剩餘勞動力以調整就業結構，並促進產業結構結構優化和經濟協調發展的政策建議。
  10. Generally, the euclidean distance and k - means algorithm can be used to clustering the time series, but it is hard to separate the time series with great different variability well

    通常可採用歐式距離及k均值演算法進行時間序列聚類，但經分析發現單憑此方法還難以實現不同變化趨勢的交通流時間序列的有效分離。
  11. Time series of discharge in neurons, that is, interspike interval ( is i ) series of action potential is considered to contain plenty of sensory information. however, there is little understanding of basic type and generating mechanism of this time coding because of the complexity of isi series

    神經元放電的時間序列，即動作電位的峰峰間期（ interspikeinterval ， isi ）序列被認為蘊含豐富的神經信息，但是由於isi序列的復雜多變，至今對這種時間編碼的基本型式及其發生機制了解很少。
  12. Since the knowledge of wto rules has been missed long time and the transparency of the related information the study needs is poor due to the organization and management system barriers, many previous studies were of cause hard to deeply and completely analyze the international competitiveness of departments, industries, regions and backward industries, hard to figure out the nature of the problems or issues and to put forward right and feasible strategy options. as to the study on the increase of the husbandry international competitiveness in all ways, there are few reports

    所構建的比較優勢與綜合指標互動式測定評價模型，不僅僅從總體角度，還結合從部門、行業、區域、相關產業的角度，通過加權、分解等途徑，全面測定評價畜牧業競爭力；不僅僅通過截面數據識別比較優勢和競爭力的現狀，還通過時間序列數據識別比較優勢和競爭力的趨勢，同時通過國際數據識別中國畜牧業比較優勢和競爭力在世界的地位現狀和趨勢。
  13. This system adopts cumulatively autoregressive moving average model [ arima ] of time series method and modified model gm ( 1, 1 ) of grey system, makes a local load forecasting modeling through the integration of the above two models and also preprocesses the daily load during the sudden change of climate, thus greatly improving the forecast accuracy. the practical operation indicates that the model is reasonable and easy to operate with complete function

    本系統在經過反復試算后，在演算法上採用了時間序列法的累積式自回歸動平均模型（ arima ）與灰色系統中的gm （ 1 ， 1 ）改進模型，並將兩種模型組合用於該地區負荷預報建模，另外還對氣候急變日負荷進行了預處理，大大提高了預報準確度。
  14. For the dynamic process of ship rolling movement, this paper analyses its dynamic date with time series analysis method and brings up this system ' s the most excellent autoregressive model ( ar model ) according to least aic criterion ( akaile, information criterion ). it reveals the regular pattern of ship rolling movement and forecasts the future value of roll angle and pitch angle, then transforms it to adjusting value of object and adjusting it according to appropriate control rules

    對于船舶搖蕩運動這一動態過程，採用時間序列分析的方法，建立系統的自回歸模型（ ar模型） ，並根據最小aic信息量判定準則保證建立的系統模型為最優化模型。利用參數模型的方式對船舶橫搖、縱搖運動的動態數據進行分析處理，揭示船舶搖蕩運動的規律，預測船舶橫搖角、縱搖角的未來值。
  15. Web - based two - dimensional and three - dimensional graphical products are generated to facilitate forecasters interpretation. model - extracted information is customized and packaged for optimal visualization, e. g. time - series forecast of surface wind, temperature, humidity, cloud cover and cumulative rainfall over hong kong

    為方便發出本地天氣預測，從模式抽出的預報資料，包括香港的地面風氣溫濕度雲量及累積雨量，更會整理成時間序列
  16. Semg signal is the sum of bioelectrical activities that recorded from the skin of working muscle by surface electrodes. the change in semg signal could reflect motor units activation patters and the status of muscle fatigue in some certain degree. because it was non - invasive and local sensitive, the technique of semg signal analysis had become very important method in examining and evaluating human muscle function

    Semg信號是從肌肉表面引導和記錄到的肌肉活動時神經肌肉系統生物電變化的一維時間序列信號，由於其檢測具有非損傷性和良好的局部性以及semg信號的變化在一定的程度上能夠反映運動單位的活動模式和肌肉疲勞的狀態，因此應用semg信號分析技術檢測和評價肌肉疲勞以及進一步探討其生理機制具有重要的理論意義和實用價值。
  17. In this part, the first work is pretreatment of a numerical model, including creating calculating grids automatically, improvement of the linear boundary technique and so on. the second work is to estimate the siltation of a basin or channel by liu ' s equation. the third work is to build an edbms ( engineering data base management system ) for the result of mathematical model

    其中主要的工作是：其中主要的工作一是數學模型的前處理，計算網格自動生成，線邊界法的優化；二是應用劉家駒公式在長江口深水航道治理工程地理信息系統的支持下實現港池、航槽開挖的實時回淤估算；三是將計算成果形成gis管理和支持下的工程數據庫系統（ engineeringdatabasemanagementsystem ） ，同時嘗試解決時間序列數據如地形沖淤變化，潮位、流速過程的分析、查詢和顯示問題，並實現實時、互動的動態演示及三維可視化。
  18. The kanerva ' s sparse distributed memory ( sdm ) tackles the problem of training large data patterns and extendes the storage mode of existing computer. but it ' s address array produced randomly ca n ' t reveal the distribution of patterns and it has ' t the ability of function approximation for its learning rule

    Kanerva的稀疏分佈存儲（ sdm ）模型解決了大維數樣本的訓練問題，推廣了現有計算機的存儲方式。但其地址矩陣的隨機預置方式不能反映樣本的分佈，並且sdm的學習方式使之不能用於函數逼近及時間序列預測問題。
  19. Inside the scope of the defined it plate, according to the theoretic mode which describes the relationship of the scale of the stock market and the incensement of economy, the paper establishes a time series regression model. in the regression equation, the independent variables are numbers of broad sense chinese it listed companies ; the dependent variables are added values of it industries

    在界定完成的信息技術板塊范圍之內，參照股市規模與經濟增長關系的理論模式，本文建立了以廣義信息技術產業上市公司數量為應變量，以該產業增加值為解釋變量的時間序列回歸模型，所取的時間截面為1992 ? ? 2000年。
  20. In chapter 2, an economic concept - location quotients ( lq ) is introduced into the mathematical part of this article, in order to isolate what a city does well, and to find which of its industries export to the rest of the nation. author manipulates last five years " lq from data on farming, forestry, animal husbandry, coal, rude oil, tourism, export and import, population and etc, argues that we could know weather there is a larger than normal concentration of activity in the region, and weather there is a trend of regular develop trace of this activity by running a time series simple autoregression, which provides a feasible analysis tool for people to judge and choose an advantageous industry within this region

    第二章，採用區位商的方式和賦予的經濟意義，通過計算，比較了過去5年中甘肅、寧夏兩省區在農業、林業、畜牧業、漁業、煤炭、原油、旅遊、進出口、人口等與資源產業密切相關的行業的區位商，並提出通過對所獲得的區位商數據建立有序的單變量時間序列回歸模型，可以獲知某項資源產業是否在該省具有明顯的優勢的計量方法，為判斷並選擇區域性的優勢產業提供了一種可行的分析工具。
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