neural process 中文意思是什麼

neural process 解釋
髓夾
  • neural : adj. 【解剖學】神經（系統）的；神經中樞的；【解剖學】背的，背側的。adv. -ly
  • process : n 1 進行，經過；過程，歷程；作用。 2 處置，方法，步驟；加工處理，工藝程序，工序；製作法。3 【攝影...
  1. Second, the process of modeling an artificial neural network has very high automaticity, for it can accomplish many inner processes automatically

    人工神經網路模型在建立過程中，自動化程度相對較高，許多內部過程可以自動完成。
  2. Application of neural network in jarosite process of zinc hydrometallurgy

    神經網路技術在濕法煉鋅礬法除鐵中的應用
  3. This article puts forward a solution named divide - assemble by deducing the size of bp neural network to overcome entering the local best point, the dividing process is that a big bp neural network is divided into several small bp neural networks, every small bp neural network can study alone, after all small bp neural networks finish their study, we can assemble all these small bp neural networks into the quondam big bp neural networks ; on the basis of divide - assemble solution, this article discusses the preprocessing of input species and how to deduce the size of bp neural network further to make it easy to overcome entering the local best point ; for the study of every small bp neural network, this article adopts a solution named gdr - ga algorithm, which includes two algorithms. gdr ? a algorithm makes the merits of the two algorithms makeup each other to increase searching speed. finally, this article discusses the processing of atm band - width distribution dynamically

    本文從bp網的結構出發，以減小bp神經網路的規模為手段來克服陷入局部極小點，提出了bp神經網路的拆分組裝方法，即將一個大的bp網有機地拆分為幾個小的子bp網，每個子網的權值單獨訓練，訓練好以後，再將每個子網的單元和權值有機地組裝成原先的bp網，從理論和實驗上證明了該方法在解決局部極小值這一問題時是有效的；在拆分組裝方法基礎上，本文詳細闡述了輸入樣本的預處理過程，更進一步地減小了bp網路的規模，使子網的學習更加容易了；對于子網的學習，本文採用了最速梯度? ?遺傳混合演算法（即gdr ? ? ga演算法） ，使gdr演算法和ga演算法的優點互為補充，提高了收斂速度；最後本文闡述了用以上方法進行atm帶寬動態分配的過程。
  4. Through the simulation of large - scale circuit simulation proved that use the crossover tearing technology could detailed network structure, simplify the diagnostic process, and the neural network can parallel deal with the diagnosis information, and the logic operation can judge the information of the multi - fault. the illustrative simulation shows that it can increase the diagnosis speed and decrease the workload before test

    通過對大規模模擬電路的模擬證明，使用交叉撕裂明細網路結構，簡化診斷過程，且運用神經網路組對信息進行并行處理，邏輯分析運算對多故障信息進行處理判斷，大大提高了故障診斷速度，減小了測前工作量。
  5. Modeling of water feeding process for sinter - mixture by modified neural network

    燒結料加水混合過程的改進神經網路建模
  6. Bfgf is essential for the proliferation and differentiation of neural stem cells, it can also affect the process of expression of rara mrna induced by atra or bmp - 2 ; 2

    Bfgf在神經幹細胞增殖與分化中都起著必不可少的營養作用， bfgf能影響al ， ra 、 bmp一2對raramrna表達的誘導
  7. This thesis introduces the working principle, craftwork requirement, modeling process, control strategies and the realization of lf refining furnance bottom blowing argon control system. through the study and analysis of bottom blowing argon process control system, the thesis discusses the mean neural network model of controlled object and the mathematical models of the exectors, pwm adjustable pressure controller and pcm adjustable flux controller according to the relevant liquid knowledge and relevant data, including design data, test data and running data. to begin with the craftwork reguirement of bottom blowing argon and the actual instance of the control system, it presents the strategies of fuzzy parameters self - adaptive pid control used in pressure difference inner loop and fuzzy plus pi compound control used in flux outer loop which are based on the above modeling in order to carry out the accurate control of argon flux

    本文介紹了lf精煉爐底吹氬過程式控制制系統的工作原理、工藝要求、建模過程、控制策略以及控制系統的實現。通過對精煉爐底吹氬過程式控制制系統進行研究與分析，並根據流體力學的有關知識以及有關數據（其中包括設計數據、試驗數據和運行數據） ，建立起了被控對象的平均神經網路模型和執行機構（即pwm調壓器和pcm調流器）的數學模型。在此模型的基礎上，從底吹氬工藝要求和控制系統的實際情況出發，提出了壓差內環模糊參數自適應pid控制策略和流量外環模糊pi復合控制策略，以實現氬氣流量的精確控制。
  8. Human bone morphogenetic protein 3 is a member of tgf - b superfamily. lt can induce the differentiation of cartilage and bone tissue in mesenchymal cell. and is important to bone self - repairment and bone development during embryo morphogenesis. in addition, some other biological activities of hbmp - 3 have also been found. such as inducing development of embryo and stimulating differentiation of neural and blood cells. therefore, there is a great prospect in the use of hbmp - 3. there is trace content of hbmp - 3 in human body. it has been expressed in the expression system of eukaryotes and prokaryotes respectively, but its application is restricted because of defects in the process and modification after translation in prokaryotic cells and higher costs and lower yields existed in eukaryotic expression system

    人骨形成蛋白3 （ hbmp - 3 ）屬于tgf -超家族的一員，可以誘導間充質細胞分化為軟骨和骨，在胚胎時期骨骼發育和骨再生修復中起著重要的作用，而且對胚胎發育過程中中胚層的誘導和分化、造血組織的發育以及神經系統的發育和修復等都起著重要作用，因而hbmp - 3有廣闊的市場前景。它在人體內含量極微，盡管研究人員已經在原核細胞和真核細胞表達系統中分別進行了表達，但是由於原核表達系統缺乏翻譯后的加工修飾，真核表達系統存在成本高、產量低等特點，限制了其在臨床上的應用。
  9. Based on the analysis of the characteristics of the raw mix slurry preparing process in alumina sintering production process, firstly, a mechanism model based on material balance principle was established as the master - rule model for the quality prediction ; secondly, considering the problem that the alkali liquor composition was unstable and its real - time measurement was difficult, a nn ( neural networks ) prediction model for the prediction of the alkali liquor composition was set up and nesting - integrated with the mechanism model ; finally, using the gray theory for the information mining from the errors of the mechanism model, a gm ( 1, 1 ) compensation model was put forward and parallel - connection - integrated with the mechanism model, achieving a raw mix slurry quality prediction model

    摘要針對燒結法氧化鋁生產過程中生料漿配料工藝的特點，根據物料平衡的原理建立機理模型，作為生料漿質量預測的主規律模型；針對堿液成分波動大且難以實時檢測的問題，對堿液成分含量建立了神經網路預測模型，並和機理模型進行嵌套集成；利用灰色理論對機理模型的偏差數據進行信息挖掘，建立了gm （ 1 ， 1 ）補償模型，並與機理模型進行並聯集成，獲得生料漿質量預測模型。
  10. Via this neural network, we can eliminate those regions which contain no plate and then use color information to modify the correct region and find the accurate position of car plate finally ; 3 ) in the progress of recognition, we apply the structural alternative covering algorithm and only use some basic techniques to process the image

    將構造性的覆蓋演算法應用於牌照的定位，在對這些區域進行分析后提取出各自的特徵並進行學習，構造出相應的神經網路，用來排除假的干擾區域，同時結合圖像的顏色信息來對前期的定位結果進行修正，最終得到正確的車牌位置： 3
  11. The evaluation of contactor performances according as dynamic characteristic curves is put forward the first time. fuzzy logic and neural network are introduced to establish a model for the contactor performances intelligent evaluation system. the model mentioned above can give a performance evaluation result in the meanwhile of the contractor dynamic process testing

    首次提出以動態特性曲線參數作為接觸器性能評判的依據，並構造了基於模糊聚類分析和神經網路演算法的接觸器動態特性性能評判模型，在實現對接觸器動態過程測試的同時，給出接觸器動態特性性能評判結果。
  12. This article describes the development process of surrogate models and introduces some experiment design methods and approximation approaches that can be used for a mdo surrogate model, they are full factorial experiment design, orthogonal experiment design, uniform experiment design, central - composite experiment design, and polynomial response surface method, kriging method, radial basis function method and artificial neural network

    為此本文中分別介紹了正交試驗，均勻試驗以及中心復合試驗等幾種試驗設計方法，以及多項式響應面， kriging ，和徑向基函數等幾種數學近似方法。並且通過構造描述機翼展向升力分佈的代理模型，對上述幾種方法作了對比分析。
  13. The content of this paper is arranged as foll owing : chapter 1 introduces the concept of credit, credit risk and credit assessment, as well as the history and development of credit assessment ; chapter 2 introduces the history of ai technology, and the background of expert system and neural network. characters and disadvantages of expert system and neural network are presented respectively and the necessity of combining expert system and neural network is lightened ; chapter 3 shows the process of dealing with sample data, including the treatment of exceptional data and factor analysis, and puts forward the concrete framework of the mixed - expert credit assessment system ; chapter 4 introduces concept of object - oriented technology, and constructs object model and functional model after analyzing the whole system. it also illustrates the implementation of concrete classes by an example of rule class and the inference algorithm in the form of pseudocode ; chapter 5 introduces the structure of the whole system, the major functional models and their interfaces, and the characteristic of the system is also generalized ; chapter 6 summarizes the whole work, and points out the remaining deficiencies as well as the prospective of this method

    本文具體內容安排如下：第一章介紹了信用、信用風險、信用評價的概念，回顧了信用評價的歷史、發展和現狀，並綜合各種信用評價模型，指出這些模型各自的優缺點：第二章簡單描述了人工智慧技術，著重介紹有關專家系統與神經網路的基礎知識，通過總結它們的優缺點，指出結合專家系統與神經網路構造混合型專家系統的必要性；本章還介紹了神經網路子模塊的概念，提出了混合型專家系統的一般框架與設計步驟：第三章對樣本數據進行處理，包括異常數據的剔除、因子分析等，提出了信用評價混合型專家系統的具體框架結構，介紹了系統知識庫的主要部分、基於優先級的正向推理機制的流程、以及基於事實的自動解釋機制的具體實現方法；第四章介紹了面向對象技術，進而採用面向對象對信用評價系統進行分析，建立了對象模型和功能模型，並在此基礎上，採用c + +語言以規則類為例說明系統中具體類的實現，用偽代碼的形式描述了推理的演算法；第五章描述了整個系統的結構，對系統主要功能模塊和界面進行了介紹，並總結系統的特點；第六章總結了全文，指出本文所構造系統存在的不足以及對將來的展望。
  14. Response surface has been built based on bp neural network with relationship of maximum of spinning force variety, material parameters and power spinning process parameters established and optimum achieved by using particle swarm optimization algorithm hence optimization of tube power spinning process parameters

    摘要以bp神經網路為基礎構建響應曲面，建立材料參數、筒形件強力旋壓工藝參數等和旋壓力最大變化值之間的關系，並用粒子群優化演算法求解，獲得符合優化條件的最優解，從而實現筒形件強力旋壓工藝參數的優化。
  15. In this paper, discrete hopefield neural network ( dhnn ) is first introduced into the field of supplier evaluation combined with analytic hierarchy process ( ahp ), meanwhile, the difficulty in expressing the indexes " weights with discrete hopefield neural network was solved

    本文首次將離散型hopfield神經網路應用於供應商評價領域，結合層次分析法（ ahp ） ，並克服了離散型hopfield神經網路難以表達各評價指標權重的缺點。
  16. 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。
  17. A combined neural network and genetic algorithm with solving stability safety of homogeneous slope was proposed and the finite element method is applied to analysis the progressive failure process of the slope and the maximum equilibrium theory, requests out stability safety of homogeneous slope with the smooth arc radius of difference with the difference below the level coordinate of arc peak, utilizing the neural network algorithm to establish slidng the nonlinear mapping relationship between level coordinate of arc radious and arc peak, being adapted the neural network algorithm to look for along the minimal stability safety of homogeneous slope and corresponding arc radious and arc peak

    提出了求解邊坡穩定性安全系數的神經網路與遺傳演算法。該方法採用有限元分析和極限平衡理論，求出不同的滑弧半徑和不同的弧頂水平坐標下的邊坡穩定性安全系數，利用神經網路演算法建立滑弧半徑和弧頂水平坐標與安全系數之間的非線性映射關系，採用遺傳演算法搜索邊坡的最小穩定性安全系數及相應的滑弧半徑和滑弧中心坐標。
  18. A neural networks model based on pca - cga - rbf was proposed to infer the mi of manufactured products from real process variables

    摘要建立一個基於pca - cga - rbf的徑向基函數網路模型，從過程變量中預則產品的熔融指數（ mi ） 。
  19. This paper presents the reliability analysis of three systems as following by using markov process theory and linear equation theory. ( 1 ) multi - sensor 2 / 3 ( g ) repairable decision - making system ( 2 ) cold standby repairable system of two components with continuous lifetime switch and priority ( 3 ) warm standby repairable system of two components with continuous lifetime switch and priority in this paper, we take an application of multi - sensor fusion in neural network, and set up the mathematic model of 2 / 3 ( g ) repairable decision - making system, which is composed of different components

    本文利用馬爾可夫過程理論、線性方程組理論以及laplace變換和laplace逆變換對以下三個系統做了可靠性分析： （ 1 ）多傳感器融合可修2 3 （ g ）表決系統（ 2 ）有優先權的開關壽命連續型兩個不同型部件冷貯備可修系統（ 3 ）有優先權的開關壽命連續型兩個不同型部件溫貯備可修系統多傳感器融合技術是近幾年發展起來的一門新興技術，已廣泛應用於軍事領域，並逐漸在航天、遙感、機械製造技術中得到應用。
  20. In the control process uses two bp network. one is used as nni recognizing the model, another as neural network control device ( nnc ). but first off - line recognizes controlled device, make sure nnc initial weights

    在控制的過程中，採用兩個bp網路，一個作為神經網路辨識器（ nni ）進行辨識建模;另一個作為神經網路控制器（ nnc ） 。
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