neural computation 中文意思是什麼

neural computation 解釋
神經計算神經系統處理信息的一種基本演算法, 即并行分佈處理。

  • 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
  • computation : n. 1. 計算，估算。2. 計演算法。3. 計算結果，得數。
  1. Secondly, the artificial neural networks and mixed evolutionary computation are employed into the mathematical simulation of complex geological structure, and with gis and visualization technique, the method of geological digital 3 - d modeling and visualization is presented. so, not only the functions of making geological section and querying spatial information could be achieved, but also the spatial distribution of geological structures and their complex relationship could be described visually. thereby an interactive and convenient way for engineering geological design could be actualized

    （ 2 ）提出了復雜地質構造數學模擬的神經網路方法與混合進化方法，並利用gis技術和可視化技術，深入研究了數字地質三維建模及其可視化方法，實現了地質三維任意剖切、信息空間查詢與管理等功能，從而為直觀描述地質構造的空間展布及其相互間的復雜空間關系，以及快捷、交互地進行工程地質設計提供了新的途徑與手段。
  2. A novel method based on artificial neural network bp algorithm to perform the parametric identification in deep foundation excavation is proposed hi the paper. taking in situs measurements as network input and parameters to be identified as network output, the network is trained with the samples obtained from fem computation

    將某些現場實測值作為網路的輸入，土層物性參數作為網路的輸出，通過有限元正分析模型取得學習樣本來訓練網路，從而達到對深基坑開挖過程中的多層土體的物性參數進行辨識的目的。
  3. With the corrected parameter files, the results indicate that the isotopic abundance in the sample can be determined within 2 % error using a hpge detector system. artificial neural networks ( ann ) are a class of models based on neural computation and have been applied to the measurement of uranium enrichment. the principles of ann methods used in uranium measurement are presented in this paper and the conditions of analysis proceedings are described

    在核保障核查測量中和實物監測中，測量對象往往是規格確定並種類有限的元件或部件，只需要關心測量對象的屬性是否發生了變化，或者對同一種類的放射性樣品的一致性做出判斷，這種要求下使用神經網路方法是比較適宜的，並且神經網路方法是與探測器和探測效率無關的。
  4. To overcome the defaults of traditional algebra - based methods such as high gain, repetitive computation and disability of real - time solution, in this paper, we propose a novel method design of observers using hopfield neural network

    為了克服傳統上用代數方法設計狀態觀測器時增益過大、重復計算以及不能滿足適時性等缺點，本文提出了一種基於hopfield神經網路的觀測器設計方法。
  5. And cmac neural network adjusts weights locally, making its approximation quickly. in addition, the output only involves in linear computation, so it is suitable for online application

    此外， cmac網路的接受域是一個階躍式的臺階函數，適合於逼近負荷和相應的網損最小的拓撲之間的不連續的關系。
  6. Point to above problems, under the financial support of the national natural science foundation ( exploration of high tech and new concept and new conceive ), the excellent young teachers program of ministry of education and national excellent doctoral dissertation special foundation, the static and dynamic real - time computation of elasticity - plastic mechanics, solving method of fuzzy finite element and other problems were studied in this paper. and some achievement was gained as following : ( 1 ) based on the positive definiteness of system stiffness matrix of finite element that was modified and the form of potential energy function of elastic body, the linear system of saturation mode ( lssm ) was introduced into the neural computation of finite element, by which the no - error solving of finite element neural net computation was realized in theory

    針對上述問題，在國家自然科學基金（高技術新概念新構思探索） 、教育部優秀青年教師資助計劃、高等學校全國100篇優秀博士學位論文作者專項基金等的資助下，本文對彈塑性力學問題的動靜態的實時計算、模糊有限元的求解方法等問題進行了系統和深入的研究，取得了以下成果： （ 1 ）根據有限元總剛矩陣經修正後具有正定性的特點以及彈性體勢能函數的具體形式，將飽和模式的線性系統（簡稱為lssm系統）引入到有限元的神經網路計算中，在理論上實現了有限元神經網路計算的無誤差求解。
  7. Evolutionary computation, neural computation and dna molecular biology technique are respectively corresponding to three different levels which are organism, nerve cell and molecular in the process of simulating brainpower. so we can see that the last method that base on simulating and studying on dna of biology is more probably to show up the essence of formation of brainpower

    從遺傳進化、人工神經網路和dna分子生物技術對智能的模擬過程看，它們分別對應生物群體、生物神經元和生物分子三個截然不同的層次，由此可以看到，基於對分子生物dna的模擬和研究將有可能更深刻地揭示智能形成的本質。
  8. Traveling salesman problem is combinatorial optimization problem in graph theory, it has npc computation complexity, and lots of problem can transfer to traveling salesman problem. the computation of tsp is analyzed, then the hopfield network method for solving tsp is given, at last we solve 10 - citys traveling salesman problem and chinese traveling salesman problem by using chaos neural network modeling

    首先分析了旅行商問題在窮舉搜索法下的工作量；其次給出了求解旅行商問題的hopfield神經網路方法，同時分析了利用人工神經網路求解旅行商問題所存在的問題；最後利用混飩神經網路模型求解10城市旅行商問題和中國旅行商問題。
  9. In designing a multi - structuring elements filter, combination rules and structuring elements of the morphological transform are determined automatically, and one kind of neural networks is taken for the filter, in optimzing structural parameters of the filter, three computation methods are designed respectively, by adopting some priori information in application fields to guide optimal structural parameter learning procedure, which are the bp adaptive learning algorithm, the heuristic genetic learning algorithm and the inductive simulated annealing learning algorithm

    在多結構基元濾波器設計中，通過學習人-機交互選定的目標樣本，自動確定形態變換的組合規則及其結構元素，最終以神經網路形式構成濾波器。在結構參數的優化學習中，利用應用領域的先驗知識，分別設計了自適應bp學習、啟發式遺傳學習和引導式模擬退火學習等三種最優化計算方法。
  10. This neural network is characteristic of fixed configuration, good understandability, simple computation and exact accuracy

    這種新型神經網路具有結構確定，可解釋性好，計算簡單，收斂速度快等特點。
  11. The uniform framework description of nature - inspired computation is presented, and described with feedback neural network and swarm intelligence algorithms

    摘要對自然計算理念給出統一的框架描述，並以反饋式神經網路和群體智能演算法為例加以具體論述。
  12. Computational intelligence and its application in water conservancy and hydropower engineering ( ph. d. dissertation ) doctoral candidate : xu shigang supervisor : suo lisheng chen shoulun ( hohai university, nanjing, 210098 ) abstract computational intelligence ( ci ) which includes evolutionary computation ( ec ), neural networks ( nn ) and fuzzy system is a new subject developing rapidly

    計算智能包括進化計算、神經網路和模糊理論，是一門正在迅速發展的學科。本文對遺傳演算法、前饋神經網路、自組織特徵映射神經網路及雜合系統進行較為系統的研究，並將成果應用於水利水電工程中，形成了理論、方法與應用研究的完整體系，其主要內容如下： 1
  13. The training of a particular neural network involves huge amount of data. to improve the speed of computation, we used the idea of grid computing to construct a distributed system

    但是因為神經計算處理的數據比較龐大，所以為了提高運算速度，我們引進了網格計算（ gridcomputing ）的結構思想，架構一個分散式系統。
  14. Girosi, f., m. jones, and t. poggio. " regularization theory and neural network architectures. " ? neural computation 7 ( 1995 ) : 219 - 269

    關于學習理論和正則化理論相互關系的一個詳盡介紹。在本講和接下來的講座中，我們會經常提到這篇文章。
  15. We are experimenting with the evolution of artifical neural networks ( anns ), hence we are combining the two fields of evolutionary computation and artificial neural networks

    我們正在進行人工神經網路（ ann ）的進化理論的實驗，因此將進化計算和人工神經網路兩個領域相接合。
  16. The circuit realization of neural computation of finite element was presented

    給出了有限元的神經網路計算的電路實現。
  17. Girosi, f. " an equivalence between sparse approximation and support vector machines. " neural computation 10 ( 1998 ) : 1455 - 1480

    文章中討論支持向量機與基礎追蹤去雜訊法之間的關系。
  18. Recommended : ? hertz, j., a. krogh, and r. g. palmer. ? introduction to the theory of neural computation. addison - wesley, 1991

    計算神經科學和神經網路的定義，古典神經網路方程式，整合與啟動神經元及平均法下的簡化。
  19. Point to the limitation of existing method, the neural computation method of finite element of elasticity - plastic mechanics was studied on the base of variational principle of the second order minimal potential energy in plastic theory. the neural network solving method of elasticity - plastic mechanics based on variational principle of the second order minimal potential energy was presented, and the neural network computation model of finite element of plastic mechanics was given

    針對已有方法的局限性，以塑性理論中的二階段最小勢能變分原理為基礎，對彈塑性力學問題的神經網路有限元計算方法進行了研究，提出了基於二階段最小勢能變分原理的彈塑性力學問題的神經網路求解方法，建立了塑性力學問題的有限元神經網路計算模型。
  20. Many models, such as back propagation ( bp ), hopfield, art, have been developed and sometimes several models have to be combined to accomplish a task. to relieve the burden of implementing those models from scratch, we developed a neural computation platform ( ncp ) containing those facilities

    正是因為越來越多的應用需要神經網路的支持，我們著手開發一個神經計算平臺，該平臺實現多種神經網路模型，例如bp模型、 hopfield模型、 boltzmann機模型、 art模型、 bam模型、遺傳演算法等等。
分享友人
分享到 Line

分享到臉書