數列模式 的英文怎麼說

中文拼音 [shǔlièmóshì]
數列模式 英文
sequencing models
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 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...
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 式 : 名詞1 （樣式） type; style 2 （格式） pattern; form 3 （儀式; 典禮） ceremony; ritual 4 （自然科...
  • 數列 : progression; series; a series of numbers arranged according to a certain rule
  • 模式 : model; mode; pattern; type; schema
  1. Compared with the market share of systems adopted by several journals in taiwan, the authors also analyze the aspers process empirically, and concluded the obstacles or opportunities to success remain with a mature submission / refereeing manner and the sufficient contributions for journals

    在臚列其它同性質之非商業軟體之基礎下，最後，以學術期刊出版應用之使用評估與需求觀點，綜結學術期刊出版走入電子化管理模式的契機與阻礙，在於能否具有成熟的投稿與評閱習慣，以及足量的期刊投稿件數。
  2. Stability of rock slopes is generally controlled by the structure of rock masses, especially the soft structure surfaces. analysis of rock mass structures is a key to establish geological models and numerical simulation and a foundation to assess the stability of rock slopes. the weak structure surfaces are mainly bedding planes, faults, joints, schistosity plane and contact zones of intrusive bodies. since they are different in genesis and scale, the rock masses are different in features and mechanical intensities. based on the combination of rock structure bodies, 15 basic modes of deformation and failure of rock slope are systematically summarized. the deformation and failure of rock masses actually result from the recombination and rearrangement of these rock bodies. there are 11 types of rock mass structures and various deformation and failure of bank slopes are present in the reservoir area of the three gorge project

    巖體結構，特別是軟弱結構面對基巖斜坡變形與破壞具有顯著的控製作用，巖體結構模式分析是建立斜坡地質模型和數學模型的關鍵和評價斜坡穩定性的基礎。巖層層面斷裂構造節理裂隙片理與劈理以及侵入體和圍巖的接觸帶等是控制基巖斜坡穩定的軟弱結構面，這些成因不同大小不一的結構面將巖體分割成性質各異力學強度不均的各種巖體結構體，構成了15種基巖斜坡變形破壞的巖體結構基本模式。不同結構體的重新組合與排列是斜坡失穩的內在原因。
  3. Fsmail adopts and implements the asynchronous event driven mechanism, with all those network i / o operations in the server working under the non - blocking style ; accomplishes object - oriented heap with the dynamic array, adapted to any type of data ; adopts the multi - queue scheduling mechanism based on a fsm, easily to fulfill the extentions of delivery funtions ; fulfills the non - blocking domain name resolvement mechanism and the caching of the resolved results ; implements the non - blocking user database management and the caching of the user data recently accessed ; uses the unified memory pool management, avoiding the memory leakage and improving the performance of the fsmail server ; lastly, implements the log management server based on the c / s mode, eliminating the inconsistency of the logging metadata and being adapted to any kind of application logging

    Fsmail採用並實現了異步事件驅動機制，所有網路i o的實現使用了非阻塞方式；以動態數組實現了基於面向對象的堆隊列，屏蔽了堆數據的非一致性；使用了基於有限狀態機的多隊列郵件調度機制，為后續版本的擴展性提供了良好的介面機制；服務器內部實現了非阻塞的域名解析機制，並實現域名地址緩存；實現了非阻塞的用戶數據庫管理模塊，並實現用戶數據緩存；使用了統一的內存池管理機制，既防止了內存泄漏，又提高了服務器的性能；最後，還實現了基於c s模式的日誌管理服務器，屏蔽了日誌數據元的非一致性。
  4. In this paper, we study focus on building intrusion detection model based the technique of data mining ( dm ). firstly, the paper designed a scheme to modeling intrusion detection based dm and bright forward the idea of descriptive model and classified model to intrusion detection. secondly, we designed and implemented a net data collection system with high performance and a scheme to pretreat net data. thirdly, after studying the algorithms to mine association rule and sequence rule in net data, we extended and improved the algorithms according to the characteristic of net data and the field knowledge of intrusion detection

    首先設計了基於數據挖掘技術的入侵檢測建模方案，提出使用該技術建立入侵檢測描述性模型和分類模型的思想，並用分類判決樹建立了入侵檢測分類模型；其次，設計和實現了一個高性能的網路數據採集系統和網路數據預處理的方案；然後，在對關聯規則挖掘和序列規則挖掘演算法進行研究的基礎上，結合網路數據的特性和入侵檢測領域的知識對演算法進行了擴展和改進，挖掘出了網路數據的關聯模式和序列模式；最後，研究了描述性模式的應用，並設計出基於模式匹配的入侵檢測引擎，該引擎具有誤用檢測和異常檢測功能。
  5. This thesis includes four parts in which the technologies of web usage mininig are systematically researched. in the first part we summarize the techniques of data mining and web usage mining, present the significance of the research on web usage mininig, the status of research and the problem which web usage mininig will face with. in the second part we discuss the web usage mininig according to the process of web mining. in the stage of data preparing and preprocessing we discuss the algorithm of data cleaning, user and session identification in detail, and present a data model of association rules and sequential patterns in the stage of pattern discovery, discuss the useful method of pattern analysis in last stage. a synthesis clustering algorithm cppc is proposed in the third part of this thesis

    本文分主要從以下四個方面對web使用挖掘進行了系統的分析和研究。第一是對數據挖掘和web挖掘進行了概述，闡述了web挖掘的意義、研究的現狀、面臨的問題。第二是討論了web使用挖掘的三個階段：在數據準備和預處理階段重點討論了數據清洗及用戶和會話識別演算法；在模式發現階段定義了關聯規則和序列模式的數據模型；模式分析階段則討論了現行的幾種分析方法。
  6. It ' s a pity that although there are many papers and articles focused on data mining published every year, most of them deal with data mining concept and abstract algorithm theory, it is hardly to see their real implementation and application, in this context, when i was in my graduate exercitation in a company in beijing, which focus on developing supermarket software, i joined and completed an olap ( online analytical processing ) project, merchandise analysis and sale report system, which based on microsoft analysis service and microsoft sql server. i also design and implement three important algorithms : merchandise association rule algorithm based on multi - level merchandise category, supermarket member customer shopping frequent sequence generating algorithm, customer classification ( decision tree ) algorithm which based on information entropy and conditional probability tree, and they all achieve expected result

    本文作者在實習期間，參與並完成了基於微軟分析服務器的銷售分析與報表系統；並在公司即將開始的數據挖掘項目中，完成了多個重要演算法的設計和c + +程序實現：基於多層分類商品樹的商品關聯規則演算法，會員顧客的購物頻繁序列模式產生演算法；基於信息熵理論和條件概率樹的會員顧客分類（決策樹）演算法，並分別使用數據進行了測試，取得了較好的結果。
  7. The empirical result of analyzing here can be concluded as follows : the error of adaptive neuro - fuzzy inference systems ( anfis ) is the smallest, multivariable fuzzy time series models is the second smallest, and grey forecasting is the third smallest

    實證結果得知在有限資料筆數下，適應性類神經模糊推論系統（簡稱anfis ）預測結果較佳，多變量模糊時間數列模式次之，灰色預測模式第三。
  8. To be dealed agaist extended data, this thesis has improved on and come true arithmetic of time sequence model, and amended conventional decision tree arithmetic, introduced the decision tree arithmetic for extended data, namely threshold value control approach. according to threshold value and concept hierarchy, threshold value control approach can set up the concise and statistic classification tree. at the same time, based on the theory of the concept lattice, this thesis introduces the arithmetic of mining association rules based on quantified concept lattice reduced by uncertainty coefficient

    針對泛化后的數據，本文改進並實現時間序列模式發現演算法；修改了傳統的決策樹演算法，提出了一種適合於泛化數據的決策樹構造演算法：閾值控製法，閾值控製法通過閾值和概念層次的控制，可以建立簡潔明了、具有統計意義的分類樹；在概念格理論基礎上提出了基於不確定系數法挖掘關聯規則的演算法。
  9. In order to overcome the present numerous methods for water prediction and the complex model, which make the actual selection of prediction methods more difficult. according to the changing characteristic of water and analysis theory of auto correlated formation, the data formation of time series was discerned, optimal selection methods for the model of water prediction were raised

    為克服目前用水量預測方法眾多，模型繁雜而給實際預測方法選擇帶來困難的情況，根據城市用水量的變化特徵，通過自相關分析理論，對時間序列的數據模式進行識別，提出了用水量預測模型的優選方法。
  10. In order to unify stored data - mining results in pattern warehouse, the author probes intensively into the storage methods of data - mining results ( association rules, classification rules, sequential patterns ). it proposes the storage methods to use the relational algebra to describe. this realizes consistent storage of data - mining results in relational database

    為使數據挖掘結果能統一存儲在模式庫中，作者對關聯規則、分類規則和序列模式挖掘結果的存儲方法進行了深入的研究，提出了數據挖掘結果模式的存儲方法，並用關系代數進行了描述，在關系數據庫中實現了多種數據挖掘結果模式的統一存儲。
  11. To solve these problems, this thesis proposed a new model for the intrusion detection system that based on the data mining. we have discussed some key technical problems and related solutions. we apply some existing algorithms of association analysis, sequence pattern analysis, and data classification to the intrusion detection system

    針對這些問題，本文採用了一種基於數據挖掘技術建立入侵檢測系統的方法，討論了該系統實現中的關鍵技術及解決方法，將現有的數據挖掘演算法中的關聯分析、序列模式分析、分類等演算法應用於入侵檢測系統，對入侵行為提取特徵、建立規則，通過對審計數據的處理與這些特徵進行匹配，檢測入侵，以形成智能化的入侵檢測系統。
  12. Incremental update algorithm of sequential patterns mining based on projected datasets

    基於投影數據集的序列模式增量挖掘演算法
  13. This tool is centered on the user, under the user " s control, and to be capable to effectively mine the rule of time sequence model and the classification rule and the association rule in the database or data warehouse

    設計並初步實現了一個數據挖掘原型系統，該工具以用戶為中心，在用戶的干預下能夠有效的對現實數據庫、數據倉庫進行時間序列模式、分類規則和關聯規則的挖掘。
  14. 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。
  15. This thesis explored the application of the forecasting methods of arima time series and multivariate fuzzy time series : two - factors models, proposed by chen and hwang ( 2000 ), heuristic models, proposed by huamg ( 2001 ), and markov models, proposed by wu et. al. ( 2003 ). this thesis employed five to sixteen intervals to instead of the method proposed by huarng ( 2001 )

    本文的研究重點在探究近期理論界提出的三種多變量模糊時間數列模型? ? chen和hwang （ 2000 ）所提出的二因子模型、 huarng （ 2001 ）所提出的引導式模型、 wu等（ 2003 ）所提的馬可夫模型，分別針對各模型的建構步驟、適用場合，及上述文獻未達到的部份，再做深入研究，並比較其結果。
  16. We introduce data mining technology in data analyzing, and extend algorithms of this system based on exploiting algorithms in data mining, such as conjunction analyzing algorithm and serial mode analyzing algorithm, which can extract security related attributes of system characteristic efficiently, promote the scalability of the system greatly and provide data support for insight research toward the system

    在數據分析中引入了數據挖掘技術，在利用數據挖掘中的關聯分析、序列模式分析等演算法的基礎上，針對本系統對演算法進行了擴展，能夠有效的提取與安全相關的系統特徵屬性，大大提高了系統的可擴展性，並且對系統的深入調查提供數據的支持。
  17. It is a hotspot that the data mining of time serial model, classify rule, association rule in the data mining study currently

    時間序列模式、分類規則和關聯規則挖掘是當前數據挖掘研究中一個熱點。
  18. We describe a serial of methods for solving problems in the discovery of recurrent patterns of alarms in database

    提出一系列方案用於解決告警數據模式發現過程中需要解決的問題。
  19. In this paper, the brief analysis is focused on the pia firstly, the four layers model and the relationship and mapping between different layers are discussed later

    它是支持并行設計的產品信息的組織和排列模式，與產品建模、產品數據管理及先進製造模式之間有著密切的關聯。
  20. The main thought is to introduce a management system of pattern base in the original data - mining systematic architecture. this management system of pattern base has three mainly function components ： pattern base - storing patterns of data mining ; management system of pattern base - managing pattern base, through management system of pattern base the users can carry on various operations and management ; monitor - offering automatically trigger mechanism, answering for automatical monitoring changed data and transfering changed data to management system of pattern base, in order to implementing automatical update of patterns by data mining again

    即在原有的數據挖掘體系結構中增加一個模式庫管理系統，該系統有三個主要的功能部件：模式庫? ?用於存儲數據挖掘得到的模式（如：關聯規則、分類規則和序列模式等等） ；模式庫管理系統? ?負責對模式庫進行管理，通過這個子系統用戶可以對模式庫進行各種操作和管理；監視器? ?提供自動觸發機制，負責自動檢測信息源中數據的變化並把這些變化上報給模式庫管理系統，以便通過模式庫管理系統啟動挖掘模塊重新進行數據挖掘來實現模式的自動更新，為模式時效性問題的解決提供了一種方法。
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