1)Neural Network model神經網絡模型
1.Application of neural network model in petroleum resource predication;人工神經網絡模型在石油資源預測中的應用
2.Artificial neural network model supporting decision-making of product procedure;支持產品方案決策的人工神經網絡模型構建
3.Urban forest remote sensing investigation based on neural network model technology in the main city of Nanjing;基于神經網絡模型技術的南京市主城區城市森林遙感調查
英文短句/例句
1.A New Model of Neural Network for Pattern Rattern Recognition一種應用于模式識別的神經網絡模型
2.Neural Network Model of Aerodynamic Interaction Effects of Rotor Wake on Fuselage for Helicopter旋翼/機身氣動干擾的神經網絡模型
3.INVESTIGATION ON NEURAL NETWORKS MODEL IN MAN--TO--COMPUTER SPEECH INTERFACES漢語人機接口中神經網絡模型的研究
4.Dynamical Behavior Analysis of Several Class of Discrete-time Neural Network Models;幾類離散神經網絡模型的動力學分析
5.High Speed (HS-K-WTA) Neural Network Model;高速（HS-K-WTA）神經網絡模型
6.Prediction of Thermal Conductivity of Wood Using Fractal and Neural Network Model;木材導熱系數的分形與神經網絡模型
7.The Model of Disease Diagosis on Cow Based on ANN and GA;奶牛疾病診斷遺傳神經網絡模型研究
8.Dynamical Analysis of Several Classes of Delayed Neural Network Models;幾類時滯神經網絡模型的動力學研究
9.Stability Analysis of a Class of Recurrent Neural Network Model;一類遞歸神經網絡模型的穩定性研究
10.Dynamic Behavior Analysis of Several Classes of Neural Network Models;幾類神經網絡模型的動力學行為研究
11.Qualitative Analysis of a Class of Neural Network Model with Two Neurons;一類二元神經網絡模型解的定性研究
12.Analysis of Dynamic Behavior of Delayed Neural Networks Models;時滯神經網絡模型的動力學行為分析
13.Fuzzy neural network based on the SAM system基于標準可加性模型的模糊神經網絡
14.BDI Model Based on Fuzzy Wavelet Neural Network基于模糊小波神經網絡的BDI模型
15.The Modeling and Simulation of Izhikevich Neural Network;基于Izhikevich神經元模型的神經網絡建模仿真
16.Optimization Model of Computer Network Based on Neural Network;基于神經網絡算法的計算機網絡優化模型研究
17.Multi-step Network Delay Prediction Model Based on RNN基于隨機神經網絡的多步網絡時延預測模型
18.Model of network attacks simulation research based on immune-based neural networks基于免疫神經網絡的網絡攻擊仿真模型研究
相關短句/例句
artificial neural network model神經網絡模型
1.The electric-thermal parameters of the bridgewire electric explosive device was measured with the non-destructive transient pulse test system,then the function tim of the electric explosive device was forecasted using the meathematical model and the artificial neural network model.通過瞬態脈沖無損檢測試驗得到橋絲式電點火頭的電熱響應參數,利用電熱響應參數分別采用數學模型和人工神經網絡模型預測電點火頭的發火時間,并與實測發火時間進行比較。
2.Based on the establishment of risk evaluation index system about engineering project investment,introduces a new method, which applies the artificial neural network(ANN) into risk evaluation, and constructs a artificial neural network model that can solve the deficiencies of the other methods.在建立工程項目投資風險評價指標體系的基礎上,提出了將人工神經網絡應用于工程項目投資風險評價中的綜合評價方法,建立了人工神經網絡模型,較好的解決了以往的評價方法中存在的人為確定權重的不足。
3.The back propagation (BP) networks mode calculating the designed lowest navigable stage is established on artificial neural network model principle.在分析影響水利樞紐下游河段設計最低通航水位因素的基礎上 ,將設計最低通航水位計算問題概括為一種非線性輸入輸出的泛函關系 ,以人工神經網絡原理建立推算水利樞紐下游河段設計最低通航水位的BP神經網絡模型 。
3)neural network神經網絡模型
1.The factors affecting the deformation of surrounding rock in tunnel are complicated and uncertain, however, neural network can not allow for the quantitative but the qualitative factors, this ability of neural network is suitable to forecast the deformation of the surrounding rock in tunnel.系統分析了影響巷道圍巖變形的因素,構建了巷道圍巖變形預測的神經網絡模型,經過改進的網絡模型具有較好的收斂性和穩定性。
2.The neural network model with input of vibration frequency about melt flow rate, crystallite structure as well as stretch strength of polymer products was established.利用實驗數據 ,分析與研究振動場振動參數對聚合物擠出制品質量的影響 ,對聚合物擠出制品的熔體流動速率、微晶結構、拉伸強度等主要性能質量指標 ,建立以振動頻率為主要控制變量的神經網絡模型 ,并引入信息分配模型 ,探討了一個網絡輸入節點下神經網絡學習樣本的特征提取與優化。
3.This article expounds the predictable principle and the method of time series and neural network models.闡述了時間序列模型和BP神經網絡模型預測的原理和方法。
4)neural network models神經網絡模型
1.In the present research,the authors converted restricted networks of combinational circuits into energy functions with discrete Hopfield neural network models, used ptimization algorithm to obtain minimum of energy functions,the test vectors of stuck faults and found fault coverage is 100 percent.介紹了用離散Hopfield神經網絡模型把組合電路約束網絡轉化為能量函數,用數學優化求能量函數的最小值,即為給定固定型故障的測試矢量。
2.This paper presents a kind of neural network models for solving quadratic minimax problems with constraints, and shows its global asymptotic stability by using LaSalle invariant principle.本文提出一種求解約束二次Minimax問題的神經網絡模型 ,給出了它的Lyapunov能量函數 ,運用LaSalle不變性原理證明了它的大范圍漸近穩定性 ,作為應用考察了L1范數極小化問題 。
5)artificial neural network神經網絡模型
1.Studies on Planthoppers Occurrence Degree with the Artificial Neural Network;稻飛虱發生程度的神經網絡模型擬合研究
2.The electric-thermal parameters of the bridgewire electric explosive device such as resistance and heat loss coefficient were measured with the non-destructive transient pulse test system under non-destructive conditions,then the no-firing current of the electric explosive device was predicated using the Rosenthal mathematical model and the back-propagation(BP) artificial neural network model.通過瞬態脈沖無損檢測試驗得到橋絲式電火工品的電阻和集總熱散失系數等電熱響應參數,利用這些電熱響應參數分別采用Rosenthal的集總熱參數模型和BP神經網絡模型方法預測電火工品的安全電流。
3.In this paper,a knowledge based artificial neural network is used to model the microstrip radial stub.本文采用基于知識的人工神經網絡模型模擬微帶徑向短截線的特性 ,利用已經具有的先驗知識減小神經網絡輸入輸出映射關系的復雜程度有效減少了訓練樣本的數量 。
6)BP neural network modelBP神經網絡模型
1.The Study on the Forecasting Methods of Urbanization level——Taking BP Neural Network Model as an Example;城市化水平預測方法研究——以BP神經網絡模型的應用為例
2.Through the establishment of water environment management information system of Supa River basin, an improved BP neural network model made for the comprehensive assessment on the water quality of the basin concerned is presented in accordance with the condition with better water quality and without any principal economic industries therein.通過建立蘇帕河流域水環境管理信息系統,針對蘇帕河流域沒有主要經濟產業、水質較好的狀況,側重于介紹建立改進的BP神經網絡模型對流域的水質進行綜合評價。
3.It is introduced that the BP neural network model of prediction of mining collapse is established based on the survey′s data and main factors at a mine field where the collapse had happen.依據某煤炭開采區的勘察資料 ,綜合考慮影響采空塌陷的主要因素 ,建立了預測采空塌陷的 BP神經網絡模型。
延伸閱讀
Hopfield神經網絡模型Hopfield神經網絡模型Hopfield neural network model 收斂于穩定狀態或Han加Ing距離小于2的極限環。 上述結論保證了神經網絡并行計算的收斂性。 連續氏pfield神經網絡中，各個神經元狀態取值是連續的，由于離散H6pfield神經網絡中的神經元與生物神經元的主要差異是:①生物神經元的I/O關系是連續的;②生物神經元由于存在時延，因此其動力學行為必須由非線性微分方程來描述。為此，在1984年J.J.H叩fi酗提出了連續氏pfield神經網絡，它可用圖1所示的電路實現，其動態方程┌───┐│·T叮 │└───┘圖1連續F砧pfield神經網絡 (a)Sigmoid非線性;(b)神經元模型可由下述微分方程式描述: 、，產 門J /r、l、1.。甕一客、一佘Ii認=f(u￡)￡=l，2，…，n式中f(·)為連續可微的Sign101d函數;T，j=兀、i，j=1，2，“’，n幾=0]=i1~.吞~·‘八文一Q*+，戮T，j‘一‘，2，”一”連續時間氏pfield神經網絡式的計算能量函數定義為:一告客客幾從硯 石l「Vi_1，、，合，，， +乞古!‘廠‘(x)dx一乙I，從(4) ’月R‘Jo“‘、一’一月一，” 對于式(3)，若f一‘為單調增且連續，C>0，T，j=幾(i，j=1，2，一，n)，則沿系統的運動軌道有dE一。-丁丁足之Uat當且僅當貸一。時 箭一。式(3)的穩定平衡點就是能量函數E〔式(4)」的極小點，反之亦然。同時，連續氏pfield神經網絡式(3)以大規模非線性連續時間并行方式處理信息。網絡的穩定平衡點對應于其計算能量函數E的極小點，網絡的計算時間就是它到達穩定的時間，網絡的計算在系統趨于穩態的過程中也就完成了。這也是式(3)用于神經計算及聯想記憶的基本原理，也即神經計算機的基本原理。HoPfield shenling wangluo moxingHopfield神經網絡模型(Hopfieldne，Ine幻即0比m側觸l)一種單層全反饋的人工神經網絡模型(后稱之為氏p玉idd模型)，它對推動人工神經網絡研究的復蘇起了很重要的作用。 且，lield對人工神經網絡研究的貢獻主要有: (l)把有反饋的神經網絡看作一個非線性動力系統，提出了系統的全局Lyap陰lov函數(或稱能量函數)的概念，用于系統穩定性的分析; (2)利用上述分析方法解決人工智能中的組合優化問題，如15護;(3)給出了利用模擬電子線路實現的連續Hopfidd網絡的電路模型，為進一步研究神經計算機創造了條件。
