連接學習 的英文怎麼說

中文拼音 [liánjiēxuéxí]
連接學習 英文
connectionist learning
  • 連 : Ⅰ動詞1 （連接） link; join; connect 2 （連累） involve （in trouble）; implicate 3 [方言] （縫） ...
  • 接 : Ⅰ動詞1 （靠近;接觸） come into contact with; come close to 2 （連接; 使連接） connect; join; put ...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 連接 : connect; fit together; link; marry; mate; joint; association trail; linkage; concatenate; concate...
  1. In addition, many other problems also exist in hardware neural network, including error problem, learning mode, parallel architecture, and also neural network inner linking problem, hidden layer and the realization of the multiplicator and etc. for instance, error problem : hardware neural network employs the limited precision, and will inevitably bring limited precision error

    另外，硬體實現神經網路還存在誤差問題，學習方式，并行結構等方面的問題，還有神經網路內部的連接問題，隱層及乘法器的實現等等。如誤差問題，硬體實現神經網路使用的是有限精度，不可避免的會產生有限精度誤差，選取合適的精度，才能既適合空間的要求，又避免對網路的實現產生一定的影響。
  2. Shapes and symmetry. go wild. piece together the sticky lines and watch zany picture puzzles come to life while you learn proportion, matching, scale and symmetry

    形狀及對稱：擺脫束縛。連接所有的線條，觀察古怪的拼圖，逐步完成，與此同時學習到比例，對比，大小以及對稱。
  3. It is very important to estimate the basic parameters in helicopter preliminary design. neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods. however, there are some difficulties in using nn, e. g., how to select a proper network structure and the number of hidden layers. in this paper, structure and connection weight of a three - layer nn are optimized by genetic algorithm, and the optimized network is applied to helicopter sizing. the proposed method can not only give an optimal nn structure and connection weight, but also reduce the prediction error and has the capability of self - learning when the latest data are available. furthermore, this method can be easily applied to helicopter design systems

    在直升機初步設計階段估算其基本參數是很重要的.神經網路的通用性和精度比傳統的估算方法有更多的優勢，但是在應用神經網路時存在如何選擇合適的網路結構和隱層節點數目等一些困難.應用遺傳演算法優化三層神經網路結構和連接權重，並將優化得到的網路應用於直升機參數選擇中.該方法不但可以給出一個最優的神經網路結構和連接權重，而且降低了估算誤差，具有及時應用最新數據學習的能力.此外，該方法易於在直升機設計系統中得到應用
  4. Practice in using linking words within a paragraph. students have to drag the linking words to the correct place within a paragraph about water conservation

    在段落中練習句子銜接。學生必須在一段關於水資源保護的段落中把連接詞放在合適的位置。
  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. By the network, a optional nonlinear input - output mapping relationship can be realized. concrete mapping relationship materialize at the distributed linking weight values between neurons that build up the ann. due to the strong self - adaptability and self - learning - ability as well as excellent and robustness and tolerance ability, it can not only replace many traditional algorithm which is very complicated and timeconsuming, but also, because the processing to information is more close to person ' s thought activity habit, it provides a new way for solving the prediction of nonlinear system and unknown model

    通過這種網路能夠實現任意的非線性輸入輸出映射關系，具體的映射關系體現在構成網路的神經元之間的分佈連接權上，由於網路具有很強的自適應和學習能力以及魯棒性和容錯能力，它不僅可以替代許多復雜耗時的傳統演算法，並且由於它對信息的處理更加接近於人的思維活動習慣，為解決非線性系統模擬和未知模型的預測提供了新途徑。
  7. Age 4 + ) construction rods connectors and the work cards are used to develop concepts of space, shapes, symmetry by building geo models. set with 48 rod, 64 clear rod, 40 cube, 12 of 6 sleeve flexible connector, 12 of 8 sleeve flexible connector, 7 of work card

    適合四歲或以上）小朋友利用小小工程棒、連接膠以及說明卡砌出不同的幾何模型，學習空間、形狀、對稱等概念，內附7張工作卡。
  8. We also prove the following properties : the stable states of the network in the same sh orbit have a same dynamical behavior, such as the size of attraction basin and the energy ; the relation of the symmetry of two isometric networks h and h ' = g - h is s ' h = g - sh - g ~ } for any isometry g, where sh and s ' h are the symmetry of h and h " respectively ; the isometry will not change the dynamical properties of the stable states set of the corresponding networks ; etc.

    ） g的對稱性s _ h和s _ n的關系為s _ h = g ? s _ h ? g ~ （ - 1 ） ；等距變換不會改變網路穩定態集的動力學性質等一系列的結論。所有這些研究結果表明了hebb學習法則是通過調整網路的連接矩陣，使得其的結構的對稱性包含存儲樣本集的對稱性這一存儲機理。
  9. In this paper, the main technology and tools for the site developing had been introduced, including the key technique of project management, the connection of database, certification of the administrator, query and modification of records and etc. at the last of the paper, an introduction about the test of the relative modules was given

    本文還介紹了系統開發的主要技術、開發環境及工具。其中詳細列舉了課程設計項目管理的關鍵技術，包括數據庫連接、管理員身份認證、課程設計項目錄入、查詢與修改等。然後，以一個課程設計項目為案例，介紹了基於本系統的學習環境和活動方式的設計，以及學習評價的設計。
  10. When estimate the connecting relation among nodes, we utilize the matching relation between enlarged neural network and xor function. this is a learning process and it is a dynamic process with ceaseless game

    在判斷節點間的連接關系時用擴大了的「神經網路」擬合異或函數，這是網路的學習過程，也是一個不斷進行博弈的動態過程。
  11. Thirdly, considering the characters of bp neural networks which is good at local minimum and bad in global optimization and the feature of ga neural networks which is bad in local minimum and good at global optimization, the paper proposes a new algorithm combined ga with bp, referred as to hybrid intelligence learning algorithm, which is applied to the problem optimizing the connection weight of the feedforward neural networks

    第三，針對bp神經網路局部搜索能力強、全局搜索能力差和基於遺傳演算法的神經網路全局搜索能力強、局部搜索能力差的特點，本文提出了一種集bp演算法和遺傳演算法優點為一體的混合智能學習法，並將其應用到優化多層前饋型神經網路連接權問題。
  12. In order to satisfy the requirement of the given precision, the connection power of the networks is studied and adjusted using the baekpropagation training algorithm ( bp algorithm )

    採用誤差反向傳播演算法（ bp演算法）對網路的連接權值進行學習和調整，以滿足給定的精度要求。
  13. The algorithms is carried into training connection weights of nn and simulation experiments show the arithmetic can escape local optima and improve learning speed of nn to some extent

    將其用於調整神經網路的連接權值，實驗證明該方法可克服神經網路訓練的局部最優解問題，並在一定程度上提高神經網路的學習速度。
  14. Ann has strong parallel running, fault - tolerant and self - learning " capacity. ann can finish the gain of knowledge by the model sampling and. memory the knowledge into the weights of topological structure

    神經網路具有很強的并行性、容錯性和自學習能力，通過對典型樣本的學習，完成知識的獲取，並將知識分佈存儲在神經網路的拓撲結構連接權值中，用來對未知樣本進行識別。
  15. It also can use to reduce the computing freedoms of the weight matrix in associative memory designing by applying the symmetry relations of the network. regarding the artificial neural network as a dynamical system with symmetry will bring the corresponding geometric approach

    利用這種對稱性關系，既可以揭示「學習就是尋找樣本集對稱性」這一學習的內涵，又可以在聯想記憶網路的分析與設計中減小連接權計算的復雜度。
  16. Based on fuzzy logic, an effective algorithm of edge connection is proposed. simulation result shows our approach can highly improve the connectivity of the extracted image boundaries without distortion. this work lays foundations of target detection, tracking, and recognition for photoelectric tracker and imaging radar

    通過理論分析及模擬結果證明，本文提出的梯度參數自學習統計的方法和基於模糊判決的邊緣連接方法能夠有效地提取邊緣點進行邊緣連接，能夠在保持原有圖像不失真的情況下，較大地提高圖像邊界的連通性，為光電跟蹤器和成像雷達的目標檢測、跟蹤和識別等提供良好的基礎。
  17. 1. the relationship between protein kinase c and remember behavior alteration of mice exposed to lead. introduction lead has high affinity to nerve and it can be accumulated in nerve tissues, which can cause long - period damage to nervous system, especially to memory and learning function

    一、慢性鉛暴露小鼠腦組織蛋白激酶c活性變化及其與記憶行為改變的關系前言學習記憶是腦的高級功能，其物質基礎是中樞神經系統高度的可塑性，包括神經網路、神經環路及突觸連接等不同水平的可塑性。
  18. Abstract : it is very important to estimate the basic parameters in helicopter preliminary design. neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods. however, there are some difficulties in using nn, e. g., how to select a proper network structure and the number of hidden layers. in this paper, structure and connection weight of a three - layer nn are optimized by genetic algorithm, and the optimized network is applied to helicopter sizing. the proposed method can not only give an optimal nn structure and connection weight, but also reduce the prediction error and has the capability of self - learning when the latest data are available. furthermore, this method can be easily applied to helicopter design systems

    文摘:在直升機初步設計階段估算其基本參數是很重要的.神經網路的通用性和精度比傳統的估算方法有更多的優勢，但是在應用神經網路時存在如何選擇合適的網路結構和隱層節點數目等一些困難.應用遺傳演算法優化三層神經網路結構和連接權重，並將優化得到的網路應用於直升機參數選擇中.該方法不但可以給出一個最優的神經網路結構和連接權重，而且降低了估算誤差，具有及時應用最新數據學習的能力.此外，該方法易於在直升機設計系統中得到應用
  19. Let the students learn how to connect a simple circuit

    讓學生學習連接簡單電路。
  20. After that until now, the research on machine learning achieved greatly, and was mainly characterized as bobbing up like a cork of algorithmic of connection learning, increasing perfected of symbol learning ; ( 2 ) the relationship between the encoding subgoal of worked example and learning

    第四階段是從20世紀80年代初開始到現在。機器學習取得了突飛猛進的成就，其特點是：連接學習演算法東山再起，符號學習日臻完善。
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