back-propagation network造句

• Application of improved back - propagation network in the evaluation of railway rock slope
  网络在岩质边坡稳定性评判中的应用
• A particularly interesting item is the back - propagation network , a c package that illustrates a net that analyzes sunspot data
  特别有趣，它是一个c程序包，说明了一个分析日斑数据的网络。
• Algorithms for defect classification are developed . classifiers are constructed based on back - propagation network . the network configuration bases on input and output
  2 .研究和开发了系统的缺陷分类方法,用bp神经网络构建了系统的分类器。
• The design theory of neural networks is discussed , including the basis principles of neuron control and the design of back - propagation network . 4
  探讨了面向控制的神经元网络设计理论，包括单神经元控制的结构和基本理论及bp神经网络设计； 4
• The back - propagation network is the core part of ahead - propagation network in artificial neural network and is widely applied in many aspects such as function approach , mode distinguishing and data condensation
  Bp网络是人工神经网络中前向网络的核心内容，它在函数逼近、模式识别、数据压缩等方面使用非常广泛。
• Thickness is an effective feature for identifying corn from monocotyledonous weed , and the correctness was 90 % . ( 6 ) six shape features were used to design back - propagation network for weed identification and the network structure was 6 - 12 - 3
  ( 6 )设计了用于杂草形状识别的bp网络，结构为6 - 12 - 3 ，并对学习误差、隐层结点数对网络性能的影响进行了研究。
• Besides stability , bifurcation and chaos in neural networks have receiving much attention recently . in this dissertation , we propose two neuron models with chaotic dynamics , which constitute chaotic neural networks that encompassed various associative and back - propagation networks
  除了稳定性之外，极限环以及混沌也是神经网络动态行为研究的重点，本文构造了具有混沌解的两种神经元模型，通过混沌神经元的耦合可以构成混沌神经网络。
• ( 2 ) combining secondary genetic algorithm with back - propagation network , the thesis redacts genetic neural network procedure , which optimizes number of hidden node and weight value and threshold value simultaneously . the procedure overcomes blindness during search , avoids falling into localminimum and increases learning accuracy
  ( 2 )编写了遗传神经网络ga - bp程序，采用二级遗传算法与bp算法相结合，同时优化网络隐层节点数和权值、阈值，既克服了寻优过程的盲目性，又避免陷入局部极小，提高了网络的学习精度。
• Because wavelet transform has forceful ability to pick - up character and artificial neural network has a strong capability to classify information . in this paper , the wavelet network has been formed by the wavelet transform , which is multi - dimension wavelet , and the artificial neural network which is back - propagation network . taking the eigenvector as an input of the wavelet network , the wavelet network can fulfill diagnosis of faults
  根据小波变鹏胞强的特征提取能力和人工神经网络经训练后具有较强的分类能力的特点，本文把多维小波与目前应用广泛的bp （ backpid刚on ）相结合酿成小波神经网络，并以表征故障的特征向量作为小波神经网络的输入。
• This thesis expounds fundamental principle and realization technique of artificial neural network and genetic algorithm , and redacts artificial neural network procedures . - ( l ) adopting batch processing high - speed algorithm , the thesis redacts back - propagation network procedure to enchance training velocity , in which learning rate and momentum parameters are modulated self - adaptably during error correction
  本文阐述了人工神经网络和遗传算法的基本原理及实现技术，并在此基础上利用matlab5 . 3编写了人工神经网络程序： ( 1 )编写了bp人工神经网络程序，采用vogl “批处理”快速算法，学习速率、动量参数在误差修正过程中自适应调节，提高了训练的速度。
• In the final part of the paper , the feasibility of applying neural networks to evaluate the performance of the columns is investigated . a three - layer back - propagation network is trained using the earthquake - resistant behavior experimental data of the columns to predict the ductility of the columns . the predicted results agree well with the test results
  在论文的最后，探索应用人工神经网络对核心柱的力学性能进行评估的可能性，利用该柱抗震性能试验的结果，训练一个三层bp网络，进行了柱抗震延性的预报，预报值和试验值吻合良好。
• Artificial neural network can be used to detect oil & gas information from seismic data . self - organizing feature map and back - propagation network are discussed firstly . aimed at issue of local optimization in back - propagation network and based on chaotic feature in logistic equation , a kind of chaos optimized artificial neural network is presented
  5 、混沌神经网络多属性特征信息智能判别：首先讨论了kohonen自组织神经网络和bp神经网络的算法和存在的问题，针对bp神经网络中梯度下降法只能达到局部最优的问题，本文根据logistic方程满混沌时轨道点的遍历性、随机性和不重复性，对神经网络权值的初值进行优化，提出一种权值初值混沌优化的改进神经网络算法。
• ( 4 ) the application of artificial neural network in the field was studied . by bp ( back - propagation networks ) neural network and rational choice of the calculation factor , the relation between the improved mixture composition and combustion rate , and that between the charge of ignition rocket and p - t curve were simulated . the model could exhibit in essence the inherent relation and the forecasted results were in good agreement with the actual testing results , which showed that the model could be used as a guide for the design of the composition and the ignition engine , and that artificial neural network could be employed in the field for the purpose of reducing experimental work of hazardous materials
  ( 4 )对人工神经网络在该领域的应用进行了研究，先后利用误差反传神经网络( bp网络) ，并选择合理的计算因子，分别对改进耐水点火药配方与燃烧速度以及点火发动机装药与p - t曲线进行了模拟，模型基本能够反应它们之间的内在联系，预测结果与实际测试结果基本吻合，模型基本能够指导药剂配方和点火发动机的设计，表明了人工神经网络可以应用于该领域以期达到减少危险品试验的目的。
• Neural network method is applied to the strength prediction . the ratio of water to cement material , the mass of fly ash and the silicon fume are regarded as network inputs and th e 28d strength is the target . the inputs and target are used to train a three layers back - propagation network
  在神经网络应用中，以水胶比、胶凝材料用量和粉煤灰掺量作为输入，以28d抗压强度作为目标输出，对一个三层bp网络进行了训练，然后利用训练后的网络对已知配比和28d抗压强度的混凝土进行了强度预测。
• In order to overcome problems arisen from the application of x fluorescence analysis into complex spectrum produced by archaeological ceramic fragments with multi - element , low content and thick ground , we have employed the artificial neural network into the research of x fluorescence archaeology and conducted three kinds of research works . as the first one , we have applied the linear olam network ( optimal linear association memory network ) and the non - linear bp network ( back - propagation network ) respectively to analyze the complex x fluorescence spectrum of archaeological samples , and taken both results of spectrum analysis to compare with each other . the second , the method of pattern recognition of bp network was tentatively used to perform intelligent identification of production places of these archaeological samples
  针对科技考古中对大量考古陶片进行产地研究时x荧光分析对多元素、低含量、厚基底考古陶片产生的复杂谱分析的问题，将人工神经网络引入x荧光考古中，进行了三方面的研究工作：一是用线性olam网络(最优线性联想网络)和非线性bp网络(误差反传导网络)分别对考古样品的x荧光复杂谱进行解谱，并比较二者的解谱效果；二是用bp网络模式识别方法对考古样品的产地进行智能识别；三是为了提高网络运算的可靠性和减小基体效应及电噪声的干扰和影响，研究并提出了三种网络学习前的谱数据预处理方法。
• This paper has introduced essential concept of artificial neural network , summarized basal theory of multilayer back - propagation network , put stress on expounding some issue on multilayer back - propagation network in practice , demonstrated the feasibility of resolving pile engineer with artificial neural network , discussed primary problems about some method and research of characteristic analysis on pile engineer these days , and analyzed data on test of single pile
  本文介绍了神经网络( ann )的基本概念，概述了多层前馈( bp )网络的基本理论，重点阐述了多层前馈( bp )网络应用中的若干问题，论证了用神经网络求解桩基工程问题的可行性，对目前桩基工作特性分析中的一些方法及研究中的主要问题进行了讨论，对收集到的单桩试桩资料进行了分析。