自適應組織 的英文怎麼說

中文拼音 [zìshìyīngzǔzhī]
自適應組織 英文
adaptive organization
  • 自 : Ⅰ代詞（自己） self; oneself; one s own Ⅱ副詞（自然;當然） certainly; of course; naturally; willin...
  • 適 : 形容詞1 （適合） fit; suitable; proper 2 （恰好） right; opportune 3 （舒服） comfortable; well Ⅱ...
  • 應 : 應動詞1 （回答） answer; respond to; echo 2 （滿足要求） comply with; grant 3 （順應; 適應） suit...
  • 組 : Ⅰ名詞1 （由不多的人員組成的單位） group 2 （姓氏） a surname Ⅱ動詞（組織） organize; form Ⅲ量詞（...
  • 織 : 動詞（編織） knit; weave
  • 適應 : suit; adapt; get with it; fit
  • 組織 : 1 （組織系統） organization; organized system 2 （組成） organize; form 3 [紡織] weave 4 [醫學] [...
  1. Evolvable hardware ( ehw ) is a kind of hardware with self - organizable, self - adaptive and self - repairable ability

    演化硬體是一種具有自組織、自適應、自修復能力的硬體。
  2. The innovations of this thesis can be summarized into three points. firstly, the average relative velocity is introducd into a novel adptive weighted clustering algorithm as one important parameter of weight, then it increases the stability and self - adaptability of cluster head. secondly, a new approach to calculating weight is suggested by integrating subjective and objective factors. it is verified by comparison with other approaches to selecting weight. thus the velocity of weight responding to the changes of network topology is increased. finally, using a som neural network to create a classifying model enables every node to learn to identify by itself the role in manet

    本文的創新點有三個:首先本文在wca和aow分簇演算法的基礎上，引入了平均相對移動速度作為權值重要的參數，提出了一種新的基於權值的自適應分簇演算法，提高了簇頭在移動中的穩定性和自適應性;其次，提出了利用主客觀綜合賦權法確定權重的權值計算方法，通過與其他權重選擇方法比較，網路結構變化的權值響應速度得到了改進;最後，論文利用自組織特徵映射神經網路建立分類模型，使得網路中的節點可以自學習地確定簇中角色。
  3. We discussed some statistical feature extraction methods, and the application of assom neural network in feature extraction

    我們研究了幾種統計特徵提取方法，和基於自適應子空間自組織映射（ assom ）神經網路提取字元的特徵提取方法。
  4. On the base of a systematical analysis about the theory of mathematical morphology and neural network, we present that the two methods have many complementary aspects : mathematical morphology has good filtering characteristic, but has not good adaptability and study ability from samples ; neural network has outstanding properties of self - organizing and self - adapting, but has not good filtering characteristic of mathematical morphology

    本文在分析了數學形態學理論和神經網路理論的基礎上，指出了兩者在信息處理中具有很強的互補性：數學形態學具有良好的濾波特性，但適應性差，不具備從圖像樣本中進行學習的能力；神經網路具有很強的自組織和自適應性，卻沒有數學形態學良好的濾波性能。
  5. Before the bp neural net forecast fire size class, it needs a process of studying from sample data. the neural net adjusts the weight value and threshold value according to the sample so as to give the linking weight value and threshold to low the difference between output from itself and the expected value

    Bp網路在應用於預測預報之前，需要一個網路學習過程，網路根據輸入的訓練（學習）樣本進行自適應、自組織，確定各神經元的連接權w和閾值。
  6. It is known that end - point driven and static configuration agent based adaptive methods can not apply to analyze extension, dynamic and complexity properties of large - scale video multicast applications. to solve this challenging problem, we develop a hierarchical adaptive architecture for large - scale layered video multicast ( halvm ) based on dynamic self - organized agent. halvm decomposes a large - scale video multicast system into a series of hierarchical sub - systems of small - scale

    該體系綜合了代理的動態自組織協議和可伸縮性視頻轉換編碼技術，將復雜的大型視頻組播應用系統的動態自適應問題分解為層次化的小型視頻組播應用子系統，由發送者、接收者和層次化代理分佈完成自適應功能，是一個擴展性能好、管理與控制效率高的自適應解決方案。
  7. 5. in the background of the design and implementation of network management system for the local network of china mobile, we have analyzed and designed detailedly the key technique, approach and software architecture of a practical network management system based on starbus, which use mhnm architecture, the scheme of managed objects arrangement, saa, gpa and practical skills achieved when we developed china post and china broadcast and tv network management systems. in the end, we summarize the main achievement of this paper and state some further work in the future

    5 .以中國移動通信網本地網網管系統設計為背景，以我們先後開發中國移動通信網本地網網管系統、廣電有線電視傳輸網網管系統和郵政網網管系統的實踐為基礎，結合多級網路管理體系結構ml江nm 、管理信息的組織策略、提取管理信息的自適應演算法saa和組預取演算法gpa ，在基於corba的分佈計算軟體平臺starbus上，詳細分析了基於corba技術實現實用的異構網管系統集成管理的關鍵技術、途徑和軟體結構。
  8. Using the tree data structure to manage the grids, the search and connectivity of data can be realized and quickened. the omni - tree structure is developed, which supports anisotropic grid adaptations in any of the coordinate directions and allows high aspect ratio cells. four separate data entities are defined, including nodes, lines, faces and cells, which is convenient to control information management in grids generation and flow calculation

    利用叉樹數據結構，實現並加速了網格生成中數據的搜索和查找；發展並提出了全叉樹和各向異性，使得網格的自適應加密可以根據需要在多個方向上任意的選擇；構造點、線、面和網格的四級數據管理模式，改善和方便了數據的有效組織和管理。
  9. The average ipc speedup is 5. 9 %. 2. adaptive stack cache with fast address generation policy is proposed by investigating stack access behavior of programs

    2 .通過對棧訪問行為的分析，提出一種棧高速緩存方案? ?快速地址計算的自適應棧高速緩存組織方案。
  10. In this paper an artificial neural network ( ann ) approach, which is based on flexible nonlinear models for a very broad class of transfer functions, is applied for multi - spectral data analysis and modeling of airborne laser fiuorosensor in order to differentiate between classes of oil on water surface

    由於ann方法適合於處理非線性系統，具有自組織、自學習、自適應和聯想能力，故通過對樣本反復訓練，能辨別各類樣本特徵差異，本論文的核心工作就是將人工神經網路（ ann ）的方法應用於激光遙感光譜數據的智能分析。
  11. Evidence suggests that the prognostic ability of the new model with high stability, when hidden nodes changing nearby input nodes and training times changing at the certain extent, is significantly better than traditional step wise regression model mainly due to the new model condensing the more forecasting information, properly utilizing the ability of ann self - adaptive learning and nonlinear mapping. but the linear regression technique only selects several predictors by the f value, many predictors information with high relative coefficients is not included. so the new model proposed in this paper is effective and is of a very good prospect in the atmospheric sciences fields

    進一步深入分析研究發現，本文提出的這種基於主成分的神經網路預報模型，預報精度明顯高於傳統的逐步回歸方法，其主要原因是這種新的預報模型集中了眾多預報因子的預報信息，並有效地利用了人工神經網路方法的自組織和自適應的非線性映射能力；而傳統的逐步回歸方法是一種線性方法，並且逐步回歸方法只是根據f值大小從眾多預報因子中選取幾個預報因子，其餘預報因子的預報信息被舍棄。
  12. In order to avoid matching the fault symptoms with the identification conditions artificially, ( fuzzy ) neural network was designed for diagnosis according to the optimal decision system. for the continuous quantitative diagnosis data such as the measurement, and the result of signal processing, a new hybrid system of self - organizing map ( som ) / fuzzy c - means ( fcm ), rough sets theory, and adaptive neuro - fuzzy inference system ( anfis ) was presented. firstly, the continuous attributes in diagnosis decision system were discretized with som or fcm

    對于連續的定量故障診斷數據（監測數據） ，以4135柴油機為例，提出了自組織映射（ som ）模糊c -均值（ fcm ） ?粗糙集?自適應模糊神經網路推理系統（ anfis ）集成的具體故障診斷實施方案：首先，應用som或fcm離散故障診斷數據中的連續屬性值；然後，基於粗糙集理論應用遺傳演算法計算診斷決策系統的約簡，按照實際需要確定診斷條件；最後，根據系統約簡設計anfis進行故障診斷。
  13. Study of field traceability of visual inspection system of iveco - body

    用於塞曼熱穩頻的自組織自適應預測控制系統
  14. It is expected to be self - adaptive to the varies of environment in minimum cost and come up with good effectiveness and efficiency

    它是一種自適應組織，以期用最小的決策總成本適應環境的不同變化，達到組織運行的高效和高速。
  15. And the experiment has proved that the integration of instruction strategy and instruction resource based on the student model can solve the problem of the personalized organization of network - based instruction resource, which can help implement the personalized instruction on network - based instruction platform

    實驗表明， sarom的基於學生模型的教學策略和教學資網路教學資源自適應研究?摘要源整合能夠提供個性化的網路教學資源，有助於實現網路教學平臺的教學資源自適應組織。
  16. The sarom firstly determines information of the student ' s personalized fancy ; with that information the personalized instruction strategy can be hence determined. then sarom chooses instruction resource that is both favorable for the implementation of instruction strategy and preferential to students as the personalized instruction resource, and further integrate the resource with the instruction strategy and present them to the students

    Sarom首先確定學生的個性喜好，根據喜好信息確定個性化教學策略，然後在教學資源庫中選取既能配合教學策略的開展，又滿足學生喜好的教學資源作為個性化教學資源，並將這些資源和教學策略結合，使之按照教學策略的安排呈現給學生，從而實現網路教學資源的自適應組織。
  17. Aiming to solve the existing problems of the personalized organization of instruction resource, this paper is going to state, by research, that personalized organization is the essential part of personalized network - based instruction ; that it is favorable for the personalized organization of instruction resource to define " instruction resource " according to the needs of personalized instruction ; that the personalized organization of instruction resource should be integrated with the instruction strategy ; that it is an applicable way for the fulfillment of the self - adaptive organization of instruction resource in network - based instruction system to integrate the organization of instruction resource with artificial intelligence and use agent to improve the intelligence of the personalized organization of instruction resource

    （ 3 ）教學資源的定義不清，不利於個性化組織。論文針對教學資源個性化組織存在的問題，經過研究認為，教學資源個性化組織是進行個性化網路教學的關鍵內容；根據個性化教學的需要定義教學資源有利於教學資源的個性化組織；教學資源的個性化組織應該和教學策略相結合；將教學資源的組織和人工智慧技術相結合，運用agent技術提高教學資源個性化組織的智能性，是網路教學系統中實現教學資源自適應組織的一種可行的途徑。
  18. Based on the above - mentioned idea, this paper provides an instruction resource model and a students model that are fit for the personalized organization of instruction resource. also, because of the priority of information acquisition of student model, it offers a general approach to integrate the instruction resource with the instruction strategy based on the student model. besides, the paper proposes a network - based its model sarom ( self - adaptive resource organization model ) using multi - agent technology which can implement the self - adaptive organization of network - based instruction resource

    論文基於這一思想，給出了適合教學資源個性化組織的教學資源模型和學生模型，利用學生模型在學生信息獲取方面的優勢，提出了基於學生模型進行教學策略和教學資源整合的一般方法，並運用該方法給出一個能進行網路教學資源自適應組織的多agent網路智能教學系統模型sarom （ self - adaptiveresourceorganizationmodel ） 。
  19. It has not only functions like self - study, orientation, organization, also avoids evaluation artificial error in process, attaining the purpose of objective evaluation

    不僅具有自學習、自適應、自組織功能，而且避免了評價過程中的人為失誤，達到客觀評價的目的。
  20. Campared with statistical analyze, it is shown that, the network structure and network output after trained rbfnn using improved rols is more reasonable than k - mean algrithm, and the control model has the property of self _ learning, self _ organization and self _ adaptive, and the control precision can be more than 90 %. on the other hand, this paper also shows that, rbfnn model can control the desulfuration process on the whole in time, and the prediction result using rbfnn model is better than statistical analyze method

    同統計分析結果比較，得出以下結論：利用改進rols演算法訓練rbf網路比k -均值演算法能夠得到更加合理的網路結構和網路輸出；利用rbfnn所建立的脫硫智能控制模型具有自學習性、自組織性和自適應性，其控制精度達到90 %以上； rbf神經網路模型基本可以對脫硫過程進行及時控制；基於rbfnn模型的預測效果優于傳統的統計分析結果。
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