知識發現 的英文怎麼說

中文拼音 [zhīzhìfāxiàn]
知識發現 英文
dmkd
  • 知 : Ⅰ動詞1 （知道） know; realize; be aware of 2 （使知道） inform; notify; tell 3 （舊指主管） admin...
  • 識 : 識Ⅰ動詞[書面語] （記） remember; commit to memory Ⅱ名詞1. [書面語] （記號） mark; sign 2. （姓氏） a surname
  • 發 : 名詞（頭發） hair
  • 現 : Ⅰ名詞1 （現在; 此刻） present; now; current; existing 2 （現款） cash; ready money Ⅱ副詞（臨時; ...
  • 知識 : 1 （認識和經驗的總和） knowledge; know how; science 2 （有關學術文化的） pertaining to learning o...
  1. Kdd ( knowledge discovery in databases ) can find out the effective, novel, latent, and apprehensible information

    知識發現（ kdd ）能夠從數據庫中識別出有效的、新穎的、潛在有用的、以及最終可理解的信息。
  2. Knowledge discovery in database is a rather active research domain that involves statistics, database, etc. it is an unusual process that finds out the effective, fresh, latent - effective mode which can be finally apprehensible

    數據庫知識發現（ kdd ）是涉及統計學、數據庫等學科的一門相當活躍的研究領域，是從數據集中識別出有效的、新穎的、潛在有效的以及最終可理解的模式的非平凡過程。
  3. 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。
  4. Knowledge discovery in databases ( kdd ) is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, statistics, neural networks, and pattern recognition

    數據庫中的知識發現（ knowledgediscoveryindatabases ， kdd ）是當前涉及人工智慧、數據庫等學科的一門非常活躍的研究領域。
  5. It improved that kdd was useful to the freight agent department and made benefit

    實踐證明，這些演算法能很好地完成知識發現任務，為貨代管理部門創造經濟效益和社會效益。
  6. Investigation on knowledge data discovery and data mining based on the real time turbogenerator ' s monitoring data

    基於汽輪機運行監測數據的知識發現和數據挖掘初探
  7. On spatial data mining and knowledge discovery

    論空間數據挖掘和知識發現
  8. Data mining and knowledge discovery in databases is a new technology for drawing knowledge from data

    數據挖掘和知識發現是從數據中獲取知識的一種新技術。
  9. Mining classification rules is a procedure to construct a classifier through studying the training dataset. it is a very important part of data mining and knowledge discovery

    分類規則挖掘則是通過對訓練樣本數據集的學習構造分類規則的過程，是數據挖掘、知識發現的一個重要方面。
  10. As an effective approach to processing incomplete, imprecise or uncertain information, rough set has been playing an important role in the area of data mining and knowledge discovery

    粗糙集作為一種處理不完全、不精確及不確定信息的有效方法，在數據挖掘和知識發現領域大有用武之地。
  11. His areas of specialization cover the development and application of intelligent spatial decision support systems, spatial optimization, fuzzy sets and logic for spatial analysis, geocomputation, spatial data mining and knowledge discovery

    他的專門研究范圍包括智能空間決策支援系統、空間優化、空間分析的模糊集合及邏輯、地理計算學、空間數據發掘及知識發現。
  12. The paper states the concept and theoretical basis of the data mining and knowledge discovery ( dmkd ) theory. it also deeply studies dmkd model that is appropriate to present chinese enterprise via the analysis of present popular dmkd models

    本文闡述了數據挖掘與知識發現（ dmkd ）的定義及所涉及到的基礎理論知識，對當前比較成功的數據挖掘模型進行了分析對比，探討了適合我國企業現狀的數據挖掘模型。
  13. Data mining and knowledge discovery in database ( kdd ) is a rapidly emerging research field, relevant to artificial intelligence, database system and statistics. it is the nontrivial process of mining the interesting, potentially useful, valid and understandable knowledge from data

    數據挖掘與數據庫知識發現（ knowledgediscoveryindatabases ， kdd ）是當前涉及人工智慧、數據庫、統計學等學科的一門相當活躍的研究領域，是從數據中提取人們感興趣的、潛在的、可用的知識，並表示成用戶可理解的形式。
  14. After the users input control tasks in three modes : natural language, electric sheet or flow char, the computer will receive the information of control demands by data mining and knowledge discovery. and then illation is leaded to select the hardware and program the software in the inner of the computer. afterward, control program is transformed in the file format of exiting simulation software by using the simulation interface and is opened in the simulation software

    用戶只需在pc機上以自然語言或繪制控制流程圖、填寫表格的方式輸入控制任務，然後在系統內部經過數據挖掘和知識發現分析得到可用控制要求信息，並自動引導推理求解過程進行硬體選型和生成相應的控製程序，最後利用模擬介面，自動將控製程序轉化為現有的控制模擬軟體的文件格式，並在控制模擬軟體中，從而用戶可以對生成的控制系統進行模擬，檢查設計的正確性。
  15. It is very urgent for people to transform them into useful information and knowledge, and apply them in business administration, production control and forecasting, etc. as a kind of technology for extracting information from large quantity of data, data mining and knowledge discovery has become a significant research problem which has important theoretical and practical values, and attracts widely attention in international academe

    世界進入信息時代，在各個領域存在大量數據，人們迫切需要將它們轉換成有用的信息和知識，以應用於商務管理、生產控制和預測等方面。數據挖掘和知識發現作為從海量數據中提取信息的一種技術，已經成為當前一個具有重要理論和應用價值的研究課題，在國際學術界引起了廣泛關注。
  16. Most knowledge discovery or data mining tools and techniques are based on statistics, machine learning, pattern recognition or artificial neural networks

    大多數的知識發現或數據挖掘工具和技術是基於傳統的統計、機器學習、模式識別或人工神經網路。
  17. University science research dss based on knowledge discovery in database

    基於知識發現的高校科研決策支持系統
  18. Sharing of geosciences information

    地學信息共享與知識發現
  19. Applying the basic theories of spatial data mining and geomorphology, taking the loess plateau of north shaanxi province, china as the research area, this dissertation explored the theories and systematic structures of geomorphologic data mining and acknowledge discovery from dems, ascertained the systematic structures of topographic factors and synthetic topographic acknowledge, as well as systemically summarized mining algorithms from dems. the author pa id more attention also to analyze the principle and algorithm of flow length, curvature, relief, the earth ' s surface incision and gully density. in this research, the elementary constitutes and mining algorithms of regional character acknowledge in the loess plateau were probed

    本研究在廣泛總結前人研究成果與研究經驗的基礎上，利用空間數據挖掘和地形地貌學的基本理論，以陜北黃土高原多地貌類型區為實驗樣區，以1 10000比例尺dem為樣本數據，探討了dem中地形地貌數據挖掘與知識發現的理論方法和體系結構；確定了宏觀和微觀地形因子、地形綜合特徵知識的體系結構；系統總結了dem基本地形因子的提取演算法，並重點對坡長、曲率、地形的起伏度、切割深度和溝壑密度因子提取的原理與演算法作了深入的分析；提出了黃土高原地區區域特徵知識的基本構成及其系統完整、科學可行的挖掘提取演算法；擴充了arcviewgis軟體平臺中dem空間分析的基本功能；實現了以delphi7 . 0為平臺的地形信息輔助挖掘系統的設計與開發；完成了對黃土高原多地貌類型區（樣區）地形信息空間分異特徵的分析。
  20. Universities must take their social and historical responsibilities earnestly by increasing knowledge, training talents, fighting against social evils, and harmonize the relationship between man and nature

    大學應該通過傳授知識、創新知識，發現人才、培育人才，批判現實、開創風氣，融合社會、協調人與自然的關系等職能的實現向社會負責和向歷史負責。
分享友人
分享到 Line

分享到臉書