連接權 的英文怎麼說

中文拼音 [liánjiēquán]
連接權 英文
connection weight
  • 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 ...
  • 權 : Ⅰ名詞1 [書面語] （秤錘） counterpoise; weight （of a steelyard）2 （權力） power; authority 3 （...
  • 連接 : connect; fit together; link; marry; mate; joint; association trail; linkage; concatenate; concate...
  1. 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
  2. The method of automatic fuzzy rules extraction based on fuzzy bp net researches hidden key attributes through deleting redundant linking weight

    建立基於模糊bp網路的自動模糊規則提取方法，它通過刪除冗餘連接權的方法尋找到網路的隱含關鍵特徵。
  3. 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。
  4. It is used to provide reference to operator of power plant. in recurrent composed bp networks, the relation of interior node is enhanced because the link weight of input layer and output layer are added, and the saturation of fault prediction is avoided by using the linear prompting function

    本文所建的用於鍋爐故障預測的遞推合成bp網路由於bp網路各層之間及輸入層與輸出層之間的連接權的增加和線性激勵函數的採用，極大地加強了內部節點的關聯能力，避免了bp網路預測的飽和性的出現。
  5. 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。
  6. In the second layer, k - nearest neighbor algorithm is introduced to ascertain searching scope firstly, and then the nerve cell function ' s parameter in hidden layers begin to be evolved in this scope. the least - square is also introduced to calculate connection power between hidden layer and output layer

    其中在第二級演化中，先用最小鄰聚法確定搜索空間，然後再在此空廣西大學頎十論文i 13f神經網路在ect圖像重注中的應用研穴間內進行演化，其中用最小二乘法來確定從隱層到輸出層的連接權值。
  7. It should be mentioned that all the results obtained in this chapter is relevant to the hypnosis that the weight matrix is symmetric. chapter 5 is made up of two sections

    而這些結果都不是以連接權矩陣具有對稱性作為前提，所以部分結果涵蓋了原有的在對稱連接權矩陣條件下的前人的一些結果
  8. Sofm neural networks is embedded into evolutionary strategy ( es ). fitness function is constructed based on the state of sofm neural networks. the sensitivity of sofm neural networks to initial weight matrix and sequence of input exemplars is overcome by the strong global optimum of es

    將sofm網路嵌入到進化策略（ es ）中，根據sofm網路的運行狀態構造es的適應性函數，利用es的強搜索能力，克服sofm網路聚類效果受輸入模式次序和網路初始連接權矩陣的影響。
  9. After you have created the endpoints that are required for your deployment, secure them by setting endpoint connection permissions by using transact - sql statements, such as grant connect and alter on endpoint

    創建部署所需的端點之後，通過使用transact - sql語句（如grant connect和alter on endpoint ）設置端點連接權限來保護它們。
  10. 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。
  11. In fact, it is a positive monotonically increasing function of the quotient of mav divided by the variance of weights

    實際上， bam的抗噪聲能力是mav和連接權方差之商的單增函數。
  12. The merits and limitations of genetic algorithms used in optimizing the connection weights of the neural network are discussed

    摘要討論了遺傳演算法優化神經網路連接權的優點及存在的局限性。
  13. 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。
  14. 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。
  15. This algorithm uses the quotient as the fitness of each individual and employs pseudo - relaxation method to adjust individual solution when it does not satisfy constraining condition any more after genetic operation

    這種方法應用遺傳演算法和準鬆弛方法來得到bam的可行解，以mav和連接權方差之商為個體適應度函數，並應用準鬆弛方法來調整不滿足約束條件的個體。
  16. Anew neural network algorithm for decision level fusion is also presented in this dissertation. the architecture of this network is novel. it is the thresholds, not the conjunction weights, which are modified, when the network is being trained

    本文還提出了一種新的神經網路演算法用於決策層融合目標識別，該網路結構新穎，網路訓練時修改的是門限而不是連接權值。
  17. 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。
  18. 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。
  19. 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
  20. The main style of the commercialization of right to personality is agreement to be used by others people. in reality, the agreement to use the personality right principally embodies evaluation for investment, image ambassador, name of sponsor, agreement of his name as company name, permission of his name, portrait as trade mark, allowing his name to register domain name by others people. the other style of the commercialization of right to personality is commercial use of the dead of personality right

    人格權商品化的利用制度是連接權利人和使用者之間利益的橋梁，許可他人使用是自然人人格權商品化的主要形式，在實際生活中，人格權的許可使用主要表現為作價投資、形象大使、贊助用名、將姓名許可他人作為商號使用、將姓名、肖像等許可他人作為商標使用、將姓名許可他人注冊為域名使用等形式，對死者人格權的商業利用是人格權商品化的另外一個主要表現形式。
分享友人
分享到 Line

分享到臉書