輸入層 的英文怎麼說

中文拼音 [shūrùcéng]
輸入層 英文
input layer
  • 輸 : Ⅰ動詞1 （運輸; 運送） transport; convey 2 [書面語] （捐獻） contribute money; donate 3 （失敗） l...
  • 入 : Ⅰ動詞1 （進來或進去） enter 2 （參加） join; be admitted into; become a member of 3 （合乎） conf...
  • 層 : i 量詞1 （用於重疊、積累的東西 如樓層、階層、地層） storey; tier; stratum 2 （用於可以分項分步的...
  • 輸入 : 1 （從外部送到內部） import 2 [電學] input; entry; entering; in fan; fan in; 輸入變壓器 input tra...
  1. Firstly, second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable. secondly, the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network, that is to say, adding last variational effect of weight value and bias value to this time and making use of variable learning rate. at the same time, this method also adopts dynamic form in the number of hidden floor node

    首先，文中將三相變壓器兩相涌流差流的二次諧波含量比和間斷角作為網路的輸入變量；其次，利用對原有bp網路訓練演算法基礎上的改進型演算法（即在計算本次權值和閾值的變化時增加上一次權值和閾值變化的影響以及採用變學習率，與此同時隱含層神經元個數採用動態形式） ，通過樣本訓練使網路結構模型達到最優。
  2. We deduce frondose algorithm of three layers bp neural networks which is used in common, and discuss several important issues in designing neural networks which is used to forecast, for example, number of hidden layer, nerve cell number of hidden layer, epoch of learning, embryonic power value, decision of node number about input and outputo at the same time, this dissertation sums up things that conventional bp algorithm is improved on considering disadvantages of it

    3推導了常用的三層bp神經網路具體演算法，討論了實際預測應用中神經網路設計方面的幾個重要問題，如隱層數、隱層神經元數、訓練次數、初始權值、輸入節點數以及輸出節點數的確定。同時，針對傳統bp演算法存在的各種各樣的缺點，文中綜述了對其改進的情況。
  3. Keeping the original structure of cbp unchanged, we add an extra node to cbp input level and assign specific values to the weights between that node and the hidden level, and then we obtain a more general model than cbp, which is icbp

    我們在保持cbp原有結構下，通過對cbp的輸入層擴充節點（ 1個）的特殊構造，以及對該節點與隱層間權值的特殊賦值，獲得了較cbp更一般的改進網路模型（ icbp ） 。
  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. The most invasive change in the 2. 6 kernels is a fundamental change of the input layer

    2 . 6內核最擾人的改變是輸入層的低級變化。
  6. The network consists of three layers : the input layer, the hidden layer, and the output layer

    文中的bp網路模型都是由三層構成：輸入層、隱含層、輸出層。
  7. 5. 2. 2 mouse configuration again because of the changes in the input layer, you may have to reconfigure the x window system and

    還是由於輸入層的變化，如果您的鼠標在2 . 6內核下不工作，您可能得重新配置x window system和
  8. The complex - valued weights between hidden and output layer are updated by solving linear system based on finding the complex - valued weights between input and hidden layer

    當輸入層和隱層之間的權值計算出來后，就可以通過求解線性方程組得到隱層和輸出層之間的權值。
  9. The percentage of dwelling units in high - rise and low - rise buildings is entered. this affects the selected ppf if an area average was selected

    輸入層數較多和層數較少的樓宇內住宅單位所佔比率，倘若選取的是面積平均值，這個比率數字將對所選取的每單位人口有所影響。
  10. In nntcs, we use artificial neural networks ( ann ) as the classifier. the recorded term frequencies form the original feature vector, matching with neurons in the input layer of ann one by one

    系統使用神經網路作為分類器，特徵詞的詞頻組成原始特徵向量，和神經網路輸入層的神經元一一對應。
  11. In the first case you will not be affected by this issue. 5. 2. 2 mouse configuration again because of the changes in the input layer, you may have to reconfigure the x window system and

    再一次地，因為輸入層的改變，如果您在升級至2 . 6的kernel后滑鼠無法正常運作的話，您也許得要重新設定x window system及
  12. The network has four layers. input layer has 16 nodes. the first hidden layer has 17 nodes ; the second hidden layer has 10 nodes and one output node. 37 projects " data is used in training samples

    網路共有四層，輸入層節點數為16個，隱含層一的節點數為17個，隱含層二的節點數10為個，輸出層節點1個。
  13. This paper describes a three - layer feedforward rough neural network which has four input rough neurons and ten input conventional neurons, five hidden rough neurons and one output rough neuron

    本文給出了三層前向粗神經網路，輸入層由4個粗神經元和10個一般神經元組成，隱層和輸出層分別由5個、 1個粗神經元組成。
  14. In the network, the input node is 64, the middle is 20 and the output is 4. we also use matlab train and simulate the designed network. finally, we designed software, which combines all the correlate theory and method list above to validate the thinking

    神經網路在漢字識別中的應用包括研bp神經網路及其改進演算法、設計漢字識別所需要的bp神經網路，即在神經網路的輸入層、中間層、隱含層採用64 ? 20 ? 4的結構，並利用matlab6 . 5對所設計方案進行模擬和驗證。
  15. In this paper, to resolve the coupling phenomena between temperature and humidity in wood drying system, a bp neural network based pid controller is proposed and applied to wood drying system. the architecture and learning algorithm of the proposed controller is more simpler and the physical meanings of the input layer ' s neurons and output layer ' s neurons are explicit. based on predefined control rules and self - learning, the bp network changs the scaling integral and differential parameters, therefore is able to control the variants using classical pid control algorithms and at the same time, decoupling control is implemented as well during the control procedure

    本文針對木材幹燥過程中溫、濕度耦合的現象，提出一種將新的基於bp神經網路的pid控制器應用於木材幹燥控制系統的方案，其結構和學習演算法相對簡單，輸入層和輸出層神經元物理意義明確；它根據設定的某一控制規律，通過網路的自學習，調整pid控制器的比例、積分和微分參數，從而利用經典的pid控制演算法得到相應各變量的控制量參與控制，並在該過程中實現解耦控制，而不用給定樣本信號進行在線的學習。
  16. It is not like expert system, which needs repeat three periods - conceptualization, formalization and improvement. in this paper, research the fault gears " three models by the vibration signal. pick up the character vector by using the wavelet packet and energy method as the ann input neural vector

    本文以齒輪箱為研究對象，在齒輪正常、齒根裂紋、齒面非正常點蝕三種模式下，對振動信號加以分析，運用「小波包?能量」法提取出信號特徵量，作為神經網路的輸入向量，採用包括有輸入層、單隱層和輸出層的bp網路。
  17. Multi - rules neural network learning part decreases the dimensions of attribute collection, to reach the goal of simplifying the input ; we stress the multi - rules learning algorithm based on fuzzy entropy rule ; at the same time, all the knowledge available is used to design the input layer, hidden layer and output layer of the neural network

    多準則神經網路部分對客戶屬性集進行維數約簡，重點介紹了以模糊熵準則為基礎的多準則學習方法，同時提出了網路輸入層、隱含層及輸出層的構造方法。
  18. Based on the concept of " layer and type ", it is designed by layer. the types lies in the layers and then the sub - layers lies in the types. based on the feature type of the parts information, all of the part information is input systematically and finally the information model matched to the process template is created

    鄭州大學碩士研究生論文摘要系統信息模型的建立是基於特徵編碼技術，從信息輸入層面的設計入手，按「層、類」思想分層設計，層中有類，類下有層;以零件信息特徵類型為依據，系統地輸入零件各類信息，最後生成與工藝模板相匹配的信息模型。
  19. Since the position indices and texture coordinates share the same frequency, they can be added to the input layout

    因為位置索引和紋理坐標使用相同的頂點個數，它們能夠被添加到輸入層次中。
  20. In the process of image compression, considering that the three or more layers bp networks have some redundancies in the weights between input layer and meddle layer so as to effect the network ' s study speed and compression quality, we bring forward a new two layers back propagation networks and it ' s arithmetic

    考慮到利用三層及三層以上bp網路對圖像壓縮，其有效信息是中間層單元上的輸出值和中間層與輸出層之間的連接權，而輸入層與中間層的連接權是冗餘的，以至於對學習速度和壓縮質量有負面影響。
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