自學習模型 的英文怎麼說

中文拼音 [zìxuéxímóxíng]
自學習模型 英文
self learning model
  • 自 : Ⅰ代詞（自己） self; oneself; one s own Ⅱ副詞（自然;當然） certainly; of course; naturally; willin...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 模型 : 1 （仿製實物） model; pattern 2 （制砂型的工具） mould; pattern3 （模子） model set; mould patter...
  1. In this paper, we study the trading model based on the project " the network market ", which was implemented by the chongqing electronic commerce inc and us. aiming at the shortage of trading model in " the network market ", we employ game theory and multi - criteria decision theory, introduce the matchmaking schema based on price and quantity into electronic commerce application, bring forward a market matchmaking trading model including five phases : market matchmaking, reinforce learning, biliteral negotiation, contract signing, contract executing. the main work and conclusion as follows : considering the behaviour of multi - buyers with multi - sellers, we realise a matchmaking model based on the price and quantity through double auction mechanism under discriminatory and non - discriminatory price situation, analyse the incentive compatibility and competitive equilibrium of the mechanism

    主要研究成果如下:針對多個買家與多個賣家的交易行為，提出一種撮合交易模型?採用價格和數量作為撮合要素，以雙重拍賣機制為撮合手段，重點研究均價和差價形式下的實現機制，並對其激勵相容性和市場均衡進行理論分析?為增強市場效率，論文提出了一種針對雙重拍賣的學習機制，它以三參數學習模型為基礎進行改進，藉助交易歷史信息，實現交易代理的自我學習
  2. Edm has some remarkable advantages over traditional models, includes using implicit causal models, self - learning capacity, weak dependence on domain knowledge, wide applicability, robustness, self - adaptability, and population - based searching, etc. tracing back its intrinsical ideas, edm is just making use of the nature ' s decision making strategy, natural selection, to solve the decision making problems faced by human or the intelligent agents

    進化決策主要利用了進化演算法與形式化計算模型相結合所具備的自動建模能力，它具有隱式因果模型、自學習、弱知識依賴、應用廣泛、穩健性、自適應和群體搜索等優勢。追根溯源，進化決策的基本思想正是利用大自然的決策機制（自然選擇）來解決客觀世界所提出的決策問題，而自然進化又是已知的能力最強的問題求解范型。
  3. Then, the change of the pressure of the concrete in the pipage is studied. lastly, the pressure losing and the error of the routine measure are discussed. chapter three discusses the fussy self - study issues based on the concrete technology the first section expounds the basic fuzzy self - study theory

    首先介紹泵送混凝土的流動特徵，接著研究泵送混凝土在輸送管中泵送壓力的變化，並分析影響泵送壓力損失的因素，從而討論常規計量方法的缺陷第三章主要是針對前章理論模型應用模糊自學習技術。
  4. 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。
  5. The author elaborates autonomous learning categories, such as brainstorming, role - play, case studies, situated learning and so on. then the author designs a synthetical e - learning model that includes establishing unit objectives, problem driven ; creating situation, learning method instruction ; self exploring, discovering problem ; collaborative inquiry in group, communication among group ; teacher instructing, communication on web ; solving problems, constructing meaning ; forming works ; summary and evaluation

    論述了頭腦風暴、角色扮演、案例研習、情景化學習等自主學習的實踐類型，嘗試設計了一種包含確立單元目標、問題驅動；創設情境、學法指導；自主探索、發現問題；小組協作探究、組間交流；教師指導、網上交流；解決問題，意義建構；形成作品；總結評價八個環節的綜合網路學習模式。
  6. Compare to common model based on the flux analysis, this model describe the traffic network more reality. moreover, the efficiency and characteristic enable the result of optimization more precision and fleetly

    與基於流量分析的交通模型相比，該模型更加準確的描述了真實交通網路的運行情況，而遺傳演算法的自組織性和自學習性保證了優化過程的高效性。
  7. To verify the effectiveness of the proposed hybrid fnn, this thesis addressed the estimation problem for the frozen point of light cyclic oil in a fluidized catalytic cracking unit ( fccu ) in a refinery. based on the sample data collected from the industrial unit, we built a soft sensor model by using an above hybrid fnn

    最後，針對某煉油廠催化裂化裝置主分餾塔輕柴油凝固點的軟測量估計問題，本文基於工業現場所採集的樣本數據，建立了混合結構神經網路模型，並討論該模型的在線自學習問題，同時與多層前向bp網路、徑向基函數rbf網路模型進行了比較。
  8. Based on cognition theory and information technology, the paper build a simulated brain model to aid creative design by integrated artificial intelligent, expert system, fuzzy logic, and knowledge mining based on database over internet. the brain model including a memory structure to save information and knowledge, and a thought strategy with some certain levels to guide activities, therefore, the intelligent activities such as learning, problem - solving and creative design could be treated as the process that utility memory in control of thought strategy

    人腦模型體系包括了在思維策略控制下的學習、設計問題解決、創新等活動，並以語義網路與神經網路結合研究並實現了知識記憶結構，在此基礎上研究了產品構成知識的生成技術，使模型可方便實現自學習、自組織、聯想存貯等特性。
  9. In this dissertation, two kinds of optimization, methods are proposed. firstly, only these linking weights corresponding to the control rules that affect the control performance significantly are updated in order to reduce the compute works and speed up the training progress. secondly, the updating step is adjusted adaptively in accordance with the error and the change of error of the system based on the t - s model to get better performance

    針對模糊神經網路控制器一般存在著在線權值調整計算量大、訓練時間長、過度修正權值可能導致系統劇烈振蕩等缺點，提出了兩種模糊神經網路控制器的優化方法：在線自學習過程中僅對控制性能影響大的控制規則相關的權值進行修正，以減小計算量，加快訓練速度；基於t - s模糊模型，根據偏差及偏差變化率大小動態自適應調節權值修正步長，抑制控制器輸出的劇烈變化，避免系統發生劇烈振蕩。
  10. In the field of application of fault diagnosis with mese, using short signal analysis technology can get characteristics vector of faults. then fuzzy reasoning and neural networks are used to construct fault diagnosis system. the fault diagnosis system analyses the characteristic vector by self - learning

    在故障診斷領域的應用研究方面，將的簡訊號最大熵譜分析與模糊推理、神經網路技術相結合，採用模糊神經網路對最大熵譜分析得到的特徵向量進行自學習的模糊推理，能夠準備識別故障類型。
  11. It possesses not only the self - learning ability and adaptability, but also the function of self - adjusting factors. based on fuzzy set, neural network theory, the fuzzy control model and fuzzy neural network control model of multi variable system are presented. based on the automatic core - welding line of shop floor control system in yangzhou radiator plant computer integrated manufacturing system ( ys - cims / sfcs ), the fuzzy logic theory was applied to the controlling device and established the main heating room fuzzy temperature controller and finally was put into practical use

    本文採用了基於神經網路技術的智能pid控制策略，設計了一類具有自學習和自調整比例因子功能的神經元網路自適應pid控制器的結構及演算法；為解決結構不確定性的復雜多變量系統的控制，基於模糊集及模糊系統、神經網路理論，建立了多變量系統的模糊控制模型及模糊神經網路控制模型；針對揚州水箱廠計算機集成製造系統車間管理與控制系統（ ys - cims sfcs ）中的實際工程問題，設計和開發了散熱器芯子烘焊自動線主烘腔溫度模糊控制器，解決了生產中長期存在的老大難問題，提高了產品質量，降低了單產能耗。
  12. In this paper, the author applied bp algorithm in this subsystem, and a model of crack detection of glass bottle is described. this model enables the detection system to enhance the capabilities of auto - learning and auto - adapting greatly by overcoming the weakness of the worse adaptability of adapting the change of the environment and the worse tolerance to mistakes of the new information

    本論文將bp演算法應用於該子系統中，建立了基於bp神經網路的「玻璃瓶口裂紋檢測模型」 ，克服了原演算法對環境變化適應的靈活性和對新信息的容錯性較差的弱點，從而使該檢測系統的自學習、自適應能力大大增強了。
  13. In the respect of neural networks control for non - linear and uncertain system, a review of some available control strategy is made. combining neural networks control and conventional control strategy supervised learning, no supervised learning and reinforcement learning neural networks self - studying and adaptive control systems for ship course control are proposed. the thesis studies particularly their characteristics

    在非線性和不確定性系統的神經網路控制方面，論文總結了一些現有的神經網路自學習控制系統，然後將神經網路和常規控制（例如pid控制、自適應控制、內模控制等）結合起來，根據船舶操縱的特點，詳細研究和分析了有監督學習、無監督學習和再勵學習的船舶航向神經網路自學習型自適應控制系統。
  14. Furthermore, utilizing the characteristic that filtering error covariance expresses filtering precision and the principle of information conservation, the dynamic and reasonable distribution of distributed tracks weight coefficient is accomplished. jerk model and strong tracking filter is organically assembled, and based on spatio - temporal synthetically analysis and lme, a self - learning estimation method of the system measurement variance is given. the method improves obviously the

    3 、將jerk模型與強跟蹤濾波演算法有機地結合，並利用時空綜合分析和極大似然估計的思想推導出了一種系統量測方差自學習修正方法，以優化強跟蹤濾波演算法中次優漸消因子和濾波增益的在線選擇，同時根據多傳感器數據融合具有改善濾波精度的性質，進而給出一種基於jerk模型的多傳感器數據融合演算法。
  15. In the paper, a bp networks is founded to show the relationship of the box girder dimensions and load ' s peculiarity with the parameters of fitting

    本文利用bp網路來建立擬合參數與箱梁模型幾何尺寸、載荷特性等之間的非線性映射關系，通過網路的自學習功能得到穩定的網路。
  16. On the base of the study of combustion characteristics of large capacity coal - fired boiler, a fuzzy comprehensive judgement model of boiler combustion stability is established. the methods of fuzzy mathematics and neural network are applied to establish the judgement model with self - studying function

    本課題在對我國大容量機組鍋爐燃燒特性進行研究的基礎上，運用模糊數學和神經網路方法建立了具有自學習功能的鍋爐燃燒穩定性模糊綜合評判模型。
  17. So the automatic description management and the references self - adjusted control can be realized. in this paper, efforts are made to real ize the optimization of description on line by introducing the learning link. in this paper, the construction, basic function, hardware and software compositions and practicing scheme of the tobacco re - dryer intelligent control system are discussed systematically

    本文系統地論述了煙葉復烤機智能控制系統的構成、基本功能、硬體結構、軟體結構及實施方案；詳細介紹了具有自學習功能的配方管理子系統、基於模糊數模型的參數自調整子系統以及用工控組態軟體citect5 . 21開發的煙葉復烤機監控系統的設計和實現方法。
  18. There are lots of non - linear systems in the nature. because classical and morden control methods have common limitation : mathematical model of the plant has to be known in advance. but in fact many plants are intricate uncentaintied and time - varying. in addition, they also are non - linear. though there are methods of system identification in control theories, the identification theories and ways of non - linear and time - varying system are not mature and systematic. it is very difficult to carry out effective real - time control. the neural networks can approximate random non - linear relations and study by itself, and it provides new thoughts and new ways for solving these problems

    由於經典和現代控制方法存在一個共同的局限性：就是要求預先知道被控對象的數學模型，但實際上許多對象具有復雜的不確定性和時變性；此外還具有復雜的非線性。雖然在控制理論中有系統辨識的手段，但是對于非線性時變系統尚無成熟的和系統的辨識理論與方法，要實行有效的實時控制就很難了。人工神經元網路有表示任意非線性關系和自學習等能力，給解決這些問題提供了新思想和新方法。
  19. Firstly, many fixed models are modeled at different operating points through mechanism analysis. an optimal model set based on the ideal of on - line learning is proposed, which included fixed models and adaptive models. when the operating point exceeds the initial modeling range, stability results are still obtained

    首先，通過機理分析，在典型工況點下建立多個固定模型，基於在線學習器思想，給出了一種優化模型集的方法，採用固定模型加自適應模型組成新的優化模型集，在運行工況超出初始建模範圍時，仍能保證系統的穩定性。
  20. In part of theory, the paper analyses the present situation of its, presents its theoretical base, constructs a teaching mode of dual - initiative, gives its structure, discuss its writing environment, provides a reference of integrating object - oriented database and ai ; in part of design, the paper combines method of fields knowledge representation, presents teaching strategy reasoning machine based on weight - generation production rule ; according to cognitive learning theory, designs a cognitive model of student which adopts approach method and historical inheritance of study, designs a model which can navigate in learning process and in hyper - text based on student ' s model and knowledge presentation, discusses the design of explanation mechanism and man - machine interface

    在理論部分，本文分析了its的現狀，提出了its的理論基礎，建構了一個雙主的教學模式，並給出了its的結構，討論了智能教學系統的寫作環境的選擇，為本文的面向對象數據庫和人工智慧的結合提供了依據；在設計部分，本文結合領域知識表示方法，給出了一個面向對象的認知的超文本的知識表示方法，提出了基於加權產生式規則的教學策略推理機；依據認知學習理論，設計了一個採用逐步逼近法的有學習歷史繼承的認知學生模型，並根據學生模型和知識表示設計一個學習過程自動導航和超文本導航的教學模型；討論了智能系統解釋機制和人機介面的設計。
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