neural computing 中文意思是什麼
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Considering the characters of bp neural network, such as the simple structure, the advisable malleability, self - fitness, self - studying, nonlinear function approximating, the considerable abilities of parallel computing, fault - tolerant and so on, the bp algorithm have been extensively applied to the areas of system modeling, pattern recognition and seismic exploration since 1986. compared with other algorithms, as the above reasons, the bp algorithm has become the most usual and efficient solutions to the artificial neural networks
由於人工神經網路中的bp神經網路結構簡單，可塑性強，具有良好的自適應、自學習、極強的非線性逼近、大規模并行處理和容錯能力等特點，自1986年rumelhart等人提出以來，被廣泛應用於系統建模、模式識別、地震勘探等重要領域。而bp演算法數學意義明確，步驟分明，是神經網路中最為常用、最有效、最活躍的一種方法。 -
In fuzzy sets, neural networks and soft computing, yager r, zadeh l eds., new york : van nostrand reinhold, 1994. 7 lai k r. fuzzy constraint processing
其原因，是由於不管哪一種數據型態，我們都可以表示成模糊限制式，再交由限制式的糊糊推理引擎進行推演。 -
Neural network control is an important mode of intelligent control, and it is widely used in branches of control science, first, the architecture and the learning rule ( error back propagation algorithm ) of multiplayered neural network which is widely used in control system are presentedo especially, the paper refers to the architecture of diagonal recurrent neural network and its learning algorithm - - - - - recurrent prediction error algorithm because of its faster convergence with low computing costo next, before introducing the neural network control to the double close loop dc driver system, the controllers of current and velocity loop are designed using engineering design approach after analysis of the system, simulation models of the system are created
神經網路控制是智能控制的重要方式之一，它廣泛應用於自動控制學科各個領域。本文首先敘述了控制系統中常用的多層前饋網路結構及演算法（ bp演算法） ，特別提及了能夠較好描述系統動態性能的對角遞歸神經網路和在用遞推預報誤差演算法訓練drnn時取得了較快的收斂速度。其次，應用工程方法分析設計了tf - 1350糖分離機的電流、轉速雙閉環直流調速系統的控制器，作為引入神經網路控制的設計基礎，並建立了系統的模擬模型。 -
We use neural network model to implement correction part, train it using the samples of history disaster data, and correct the computing result of the former, then get the ideal result, which improves the prognostication precision. the property loss evaluation method targets insurance item as evaluation object. by using the collected data effectively, it builds a model using the method of rbf neural network, and this model is used to evaluate the property loss
災情修正部分採用神經網路模型，以歷史災情情況為樣本進行訓練，對前面計算的結果進行修正，從而得到理想的結果，使得預測精度進一步提高；財產損失評估方法以保險標的為評估對象，有效利用收集到的信息，運用rbf神經網路方法建立模型並進行財產損失評估。 -
Computing vibrational modal parameters by neural network
基於前饋多層神經網路的振動模態參數計算 -
In 1991, he introduced the concept of soft computing, the principal constituents of which are fuzzy logic, neural network theory and probabilistic reasoning
一九九一年澤德教授提出軟計算的概念，內容主要包括快思邏輯、神經網路理論及概率推理。 -
First, the basic theory of the competitiveness is analyzed, evaluating indexes which conclude relative and absolute indexes basic on the last literatures are set up. second, because the data are too many and computing time is too long, the competitiveness of science and technology of 30 areas are clustered using fuzzy clustering model, the areas of the whole nation are clustered several kinds and we can draw some conclusions of same kind. evaluating the competitiveness using single model can produce white noise, so combinational models which concluding neural network, fuzzy theory and genetic algorithm are brought forward to evaluate the competitiveness of areas which are in the same kind with fujian province in the test
本文首先分析科技競爭力的基本理論，並根據以往研究科技競爭力文獻，建立包含絕對指標和相對指標的評價科技競爭力評價指標體系，其次，針對評價福建省科技競爭力在全國范圍內的排名情況數據較多，計算時間較長的具體情況，利用模糊神經網路模型對全國30個省市自治區科技競爭力水平進行聚類分析，將科技競爭力水平接近的地區聚為一類，得出科技競爭力水平相近地區情況，而後，針對已有文獻科技競爭力評價只是利用單一模型可能產生噪聲，影響評價結果，並且主觀性較強的缺點，本文將神經網路、模糊數學、遺傳演算法等智能演算法組合，利用組合評價模型對福建省和與福建省同在一類的其它地區的科技競爭力水平進行橫向、縱向評價，得出福建省在全國范圍內的科技競爭力水平排名。 -
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。 -
By applying " none homogeneous multi - laminate element ", hong - kou rcc gravity dam ' s simulation computing of temperature field and stress field at construction period and operation period for all courses and many factors. e. some kinds of methods are discussed in detail for temperature field back analysis, and artificial neural network method for back analysis of thermal parameters of concrete is suggested
應用「非均質層合單元法」實現了洪口碾壓混凝土重力壩施工期、運行期全過程多因素的溫度場及徐變應力場的模擬計算，進行多方案的比較分析，推薦出優選溫控防裂方案，取得了非常滿意的成果。 -
The innovation of the thesis as follows : advances the generalized computing theory that combines symbolic computing with neural computing, fuzzy computing and evolutionary computing
本文的價值在於：提出了融符號計算、神經計算、模糊計算和演化計算於一體的廣義計算理論。 -
Here, we focus on four topics f artificiaj neural 3 : etwork ( ann ), swarm intelli - gence ( si ), evolutionary algorithjn ( ea ) and dna computing
本文探討4個主題：人工神經元網路，群體智能，演化演算法和dna計算。 -
Soft computing includes artificial neural network, fuzzy logic, evolutionary algorithms, rough set ( rs ) theory, etc. as a new soft computing, rough set can analyze and handle imprecise, inconsistent and incomplete data efficiently. in addition, connotative knowledge and latent rules will be discovered by using rough set theory
粗糙集理論是一種較新的軟計算方法，它能有效地分析和處理不精確、不一致、不完整等各種不完備信息，並從中發現隱含的知識，揭示潛在的規律，是一個強大的數據分析工具，具有良好的容錯性能。 -
In the last chapter, a neural computing algorithm for bit rate control is designed
在本文最後一章里，提出一種利用神經計算進行視頻輸出碼率控制的演算法。 -
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。 -
In the engineering application of ci, two methods of evolutionary computing and neural computing the fourier factors are proposed which redound to the application of fourier transformation to the engineering
在計算智能的工程應用方面，本文提出了fourier系數的進化計算和神經計算兩種智能計算方法，為fourier變換的工程應用提供了方便。 -
In this paper, the artificial neural networks are considered as a structure set of the neurons. based on this point of view, we make a comprehensive and deep researching on the hopfield model neural network of associative memory with hebbian learning in three aspects, i. e., analyzing, describing and computing of the symmetry of the system, thus discovering the storing mechanism of the hebbian learning rule. which give a deeper understanding to the associative memory mechanism of artificial neural network
本文將人工神經網路視為神經元的結構集，並從這個基本觀點出發，從三個方面，即對稱性的分析、表示以及計算，對hebb型的離散hopfield模型神經網路進行全面的、深入的研究，揭示了hebb法則這種特殊的存儲規則的機理，並以此來達到加深對整個網路的聯想記憶機理認識的目的。 -
Knowledge purification is the key procedure of knowledge acquisition, and machine learning is a effective method to gain wisdom for computers, among which artificial neural network with tutor coached can learn more accurate knowledge by faint structure, and then is a perfect way to deal with misty knowledge by describing and computing intangibly. lt is hard to describe or compute the misty relation of terms and document sort with accurate way. and we can figure out misty knowledge with misty way, so the paper introduces ann into vcm to form a conjoint method vcm ann
。其中，有導師指導的人工神經網路能夠以模糊的結構學習較為精確的內容，是將模糊的知識進行模糊計算和模糊描述的理想方法。詞條項與文檔類別之間的模糊關系難以用精確的方法進行精確地描述與計算，模糊的知識用模糊的方法能得到較好的解決，因此本文將神經網路應用到信息檢索模型中，將之與向量空間模型相結合，形成了一種改進的向量空間模型vcmann 。 -
It can complete the logic deduction procession using the theory of neural computing. last, the different functional parts of the diagnosis system are discussed
最後，本文分別介紹了該故障診斷系統的各功能模塊，並完成了診斷系統的合成。 -
Neural network ensemble can significantly improve the generalization ability of learning systems through training a finite number of neural networks and then combining their results. it is not only helpful for experts to investigate machine learning and neural computing but also helpful for engineers to solve real world problems using neural network techniques
神經網路集成通過訓練多個網路並將其結論進行合成，可以顯著地提高學習系統的推廣能力，它不僅有助於專家對機器學習和神經網路的深入研究，還有助於工程技術人員利用神經網路技術來解決現實世界中的問題。 -
As in nature, the network function is determined largely by connections ( weights ) between elements, so that a particular input leads to a specific target output. the cores of backpropagation neural network are the capacity of parallel computing, distribute saving, self - studying, fault - tolerant and nonlinear function approximating. input vectors and the corresponding target vectors are used to train a network until it can approximate a function, associate input vectors with specific output vectors, or classify input vectors in an appropriate way as defined by you
人工神經網路是一類模擬人類神經系統的結構，他揭示數據樣本中蘊含的非線性關系，大量處理單元組成非線性自適應動態系統，具有良好的自適應性、自組織及很強的學習、聯想、容錯和抗干擾能力，在不同程度和層次上可模仿大腦的信息處理機理，可靈活方便的對多成因的復雜未知系數進行建模。
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