multiple time-series 中文意思是什麼
multiple time-series
解釋
多重時間序列-
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。 -
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。 -
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。 -
By taking advantages of epipolar line features and depth discontinuities in reference 中國科學院 軟件 研究所 博士 學位 論文 基于 圖 象 的 快速 繪制 技術 的 研究 images ， an efficient inverse wmping algorithm is pfoposed in chapter 3 for gcnerating nagcs of novel views by combining multiple eference images 帆 enhm different vie 呷 oints because continuous segnents determi 。 d by pairs ofedge pixels at co 。 spending epipolar lines are order kept ， only pairs of edge pixels in the reference 渝 明 e e necess 叨 口 cowute to obtain generalized disparity of all points in the desired image as a result ， sighficant acceleraion could be made in the endering pfo 比 鴕 two accelerating techiq 此 s e presented in this algori 山 mb accelerate the hole illing process his algorithm extends the reference images rom projection of single col ： ii ’ ected surface in previously developed nvnverse w 出 下 er to ima 驢 s captured rom complex scene in chapter 4 ， an 《 dent ibr method is prese 庇 仙 y takn ull 訕 antage of 呷 bies c 咖 the method can simulate the 3d details on sllri ： ace of object successfully he 。 叩 proach ， called rered ature mopmp consists of two pans at fst ， an origi 。 ltexture with orthogonal displacements per pixel is deco 啊 osed into a series of new t6 刀 mfcs with each 他 lug a given displacement per pixel ， called ae ， ea atures ， or lt hen hese lt e used to render the novel view by conventional texture mapping d avoid gaps n the endered hlla 驢 ， some phels are to be interpolated nd extended in the 廠 kaccoding to the depth differe eee between two neighbor pixels in the original texture as these ltlt fc … e much storage nd therefore much time is equired to install ltlt into the text ’ ufc buffec an 舊 thod is pfoposed to co 呷 fcss the ltlt ， nd the cottcspondingfclldering method is given experimental esults show that the new method is efficient ， especially n rendering those objects with a smaller depth rnge compared withtheir size ， such as relief surfaces of building
與己有的三維變換方法相比較，該方法不但成功地填補了由於投影區域擴張而產生的第一類空洞，而且成功地填補了由於空間深度非連續物體相互遮擋而產生的第二類空洞，從而方便地實現了虛擬環境中的漫遊；基於物體表面深度的連續性，本文提出了一個位移預測方法? ?此方法可以從單幅參考圖象獲得逆映射過程中所需要的目標圖象的位移信息，從而大大提高了演算法的效率：與通常的正向映射演算法相比，此演算法克服了多幅參考圖象所帶來的計算量成倍增長等問題，而且誤差較小。 2 ）基於極線幾何的快速逆映射演算法。利用參考圖象的邊界信息與隱含的遮擋關系，以及極線幾何的性質，本文第三章提出了一個基於極線幾何的快速3 『一中國科學院軟體研究所博士學位論文基於圖象的快速繪制技術的研究逆映射演算法，從多幅參考圖象精確合成當前視點目標圖象。 -
, in addition, 1 design a data miner by use of vc + +, and it is successful to mine the multiple time series of medical data streams, temperature data streams and air pressure data streams
我還用vc成功設計了一個挖掘器，並對由醫院門診數據流、氣溫變化數據流、氣壓變化數據流組成的多流時間序列進行了挖掘，證明了twma是可行。 -
Based on the discussions of the conventional and recent methods of short term load forecasting such as time series, multiple regression approaches and artificial intelligence technologies, this paper presents a hybrid short term forecasting model which combines the artificial neural network ( ann ) and genetic algorithm ( ga ). in order to improve the convergence speed and precision of the back - propagation ( bp ), a new improved algorithm - the adapted learning algorithm based on quasi - newton method is given
本文首先分析比較了電力系統短期負荷預測的傳統方法時間序列法和回歸方法以及最近的專家系統和神經網路技術的優點和不足，然後針對人工神經網路bp演算法的不足對其進行了改進，採用了基於擬牛頓的自適應演算法，它提高了網路學習效率，具有較快的收斂速度和較高的精度。接著提出了改進的遺傳演算法來改善神經網路的局部收斂性。 -
After that, we designed a new data model, called inter - related successive trees irst, to find frequent patterns from multiple time series without generation lots of candidate patterns
在挖掘演算法實現上，根據序列特徵模式的有序性和重復性，提出了一種無須生成大量的候選模式集的互關聯后繼樹挖掘演算法。 -
After that, we designed a new data model, called inter - related successive trees irst, to find frequent patterns from multiple time series without generation lots of candidate patterns. experiment illustrates that the method is simpler and more flexible, efficient and useful, compared with the previous methods
在挖掘演算法實現上，根據序列特徵模式的有序性和重復性，提出了一種無須生成大量的候選模式集的互關聯后繼樹挖掘演算法，極大地提高了挖掘效率。 -
We have combined qualitative analysis and quantitative analysis to foresee the market size. firstly, we found the relative factors influencing the truck market through qualitative analysis and picked up several main factors by quantitative analysis, such as highway mileage, social fixed assets investment capital and consumption expenditure, etc. secondly, we set up four models by using those factors. the four models are a time series model, a multiple regression model, a factor regression model and an integrated model
首先，通過定性分析找到了影響我國載貨汽車保有量的相關因素，接著又進一步進行定量的分析，從而確定了公路里程數、基本建設固定資產投資額和我國社會消費支出額等為主要影響因素;然後，利用前面的分析結果構造了三個模型，即時間序列模型、多元回歸模型和因子回歸模型，並綜合幾個模型的優點建立了一個綜合的預測模型，這一部分也是全文的重點部分;最後，分析比較了各模型的優劣並給出了每個模型的適用情況。 -
Multiple time scales analysis of runoff series in hanjiang river with wavelet transform
基於小波變換的漢江徑流量多時間尺度分析 -
Multiple index comprehensive evaluation with time series of public corporations
上市公司經營業績的時序多指標綜合評價 -
2. research of mining relationship patterns in multiple time series an algorithm for discovery frequent patterns in multiple time series will be proposed
2 ）多時間序列間關聯模式挖掘研究針對更有分析價值的多序列關聯模式，進一步提出一種新穎的關聯模式挖掘方法。 -
What this difference causes in maths is that the iterative sequence of the common nonlinear time series model develops one markov chain on general state space or multiple markov chain, while the iterative sequence of nonlinear time series models 1, 2, 3 in random environment have not possessed such better nature
這個不同之處在數學上引起的後果是：一般非線性時間序列模型的迭代序列形成一個一般狀態馬爾可夫鏈或多重馬爾可夫鏈；而隨機環境下的非線性時間序列模型1 ， 2和3的迭代序列，卻無此良好的性質。 -
The method first segments time series based on a series of perceptually important points, use segment dynamic time warping distance as measurement, and then time series are converted into meaningful symbol sequences in terms of the segment ' s features and math categorization. after that, use above index model - irst, to achieve fast similarity retrieval in multiple time series
該方法提出通過基於重要點分段技術的分段動態挖掘距離作為相似性度量，既保證了度量的魯棒性，又減少計算復雜度；利用各個分段的抽取六個主要特徵，將時間序列轉化成一種特定的符號序列，在此基礎上利用海量全文索引結構實現了相似性的索引查找。
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