神经网络算法

  • 网络neural network algorithm;NNA
神经网络算法神经网络算法
  1. 一种基于改进的BP神经网络算法的布匹瑕疵分类器

    A Fabric Flaws Classifier Based On Improved BP Neural Network Algorithm

  2. 基于BP神经网络算法的弹药需求仿真研究

    Simulation of Demand of Ammunition Based on BP Neural Network Algorithm

  3. 应用BP神经网络算法对运动成绩预测的实证研究

    Demonstration on the Athletic Achievements Forecasting Based on Back Propagation Neural Network

  4. 自联想神经网络算法在X射线复合谱分析中的应用

    Application of Self Associative Memory Neural Network Algorithm in Analyzing Composite Spectra of X Ray

  5. 其中,有施教者的学习算法在多Agent系统中应用最为普遍,比如人工神经网络算法和决策树算法等。

    In Multi-Agent Systems , supervised learning algorithms are widely used such as the Artificial Neuron Network and Decision Tree .

  6. 研究了BP神经网络算法对空中目标进行威胁排序的方法。

    Threat sequencing for aerial target based on BP neural network is researched in this paper .

  7. 结合本系统的实际情况,研究了神经网络算法,尤其对具有动量项的BP算法进行了详细的说明。

    Researches neural network algorithm combined with this project , especially the BP algorithm with momentum item .

  8. 利用遗传神经网络算法的ATM链路容量控制

    Link capacity control of ATM using genetic neural network algorithm

  9. 神经网络算法在Turbo码译码错误检测中的应用

    Application of Neural Networks Algorithm in Turbo Decoding Error Detection

  10. 与传统的多元统计算法和基本BP算法的结果进行的对比后,证明本文采用的遗传-自适应神经网络算法在计算速度和精度方面都有显著提高。

    The result is compared with traditional BP and linear multi-variant analysis to testify that iterative speed and accuracy is much better .

  11. 对BP神经网络算法进行了适当的改进,并提出了几种新的改进方法,得到了良好的效果。

    The algorithm of the BP network technique is improved appropriately . Several new improving methods are developed and lead to good results .

  12. 基于神经网络算法的实时DES监督控制

    Supervisory Control of a Class of Real Time DES Based on Neural Networks Algorithm

  13. GABOR小波神经网络算法及其在灰度图象目标识别中的应用研究

    GABOR Wavelet Neural Networks Algorithms and an Application Study on Gray Image Target Recognition

  14. 利用EDA技术,采用自顶向下的设计方法,通过FPGA硬件技术实现了BP神经网络算法。

    Using EDA techniques and top-down design methodology , it achieves the BP neural network algorithm in hardware by FPGA technology .

  15. 将改进型BP神经网络算法应用于打浆度的测量,建立起打浆度的BP网络软测量模型。

    The improved BP neural-network algorithm is applied in the measurement for beating degree . The relative BP neural-net-work soft sensing model of beating degree is established .

  16. 控制系统的硬件采用了DSP芯片,以保证系统的实时性;软件采用了模糊-神经网络算法,以克服系统模型的不确定性。

    DSP chip is applied in hardware design to ensure real-time performance of control system , and fuzzy-neural network algorithm is adopted to overcome uncertainness of control model .

  17. 与此同时,本文探讨了数据挖掘技术的应用现状、决策树的生成算法和剪枝技术以及BP神经网络算法的相关知识。

    At the same time , it discusses the present status of data mining application , the decision-tree generation algorithms , pruning techniques and back propagation neural network algorithm .

  18. 在对提供个性化的学习内容时,文中利用BP神经网络算法来判定学生的学习情况,进而有针对性的推荐下一步学习内容。

    In the provision of personalized learning content , this article used neural network algorithm to determine student learning and then targeted learning content to provide the next step .

  19. 提出了自适应学习率及动量因子的BP神经网络算法和误差逼近度渐近收缩学习的BP神经网络算法,并将其应用于汽轮发电机组振动故障诊断与识别。

    The improved BP algorithms based on adaptive parameters adjustment and error contracting gradually are presented , which are applied successfully to fault diagnosis of steam - turbine generator unit .

  20. 提出了对传统EBP神经网络算法的改进方法。

    The improved EBP neural network algorithm is used in this system .

  21. 笔者论述了如何将此方法应用于中厚板轧制过程的规程制定,并提出了一种将BP神经网络算法用于预报轧制力,进行范例调整的方法。

    How to apply CBR method to establishing plate rolling regulations was described , and a new method using BP nerve net algorithm to predict rolling pressure and to regulate case was put forward .

  22. 接下来从设计思想入手,采用向量空间模型和BP神经网络算法作为文档智能分析的手段,提出了一个实现网络智能过滤的系统架构。

    Starting with the design thought , we use vector space models and BP neural networks as the way of intelligent text analysis , and put forward a system frame realizing intelligent network filtering .

  23. 最后,在分析虚拟企业集成模型地协作和生态化构建技术的基础上,应用BP神经网络算法进行模型的仿真运算,并取得了令人满意的结果。

    And finally , it present a collaboration mode and niche 's ecological constructing technology based on the BP neural network , the effectiveness of the proposed method was verified through a simulation example .

  24. 建立了基于改进的BP神经网络算法的健康指导生成模型,并应用MyEclipse,SqlServer,Tomcat等开发工具实现系统模式架构。

    The MyEclipse health guidance generation model based on improved BP neural network algorithm and application development tools such as SQL Server , Tomcat system mode architecture .

  25. 本文首先介绍了一些成熟且常用的河涌水质模型,然后分析了几种常用的河涌水质预测方法,其中重点研究了BP神经网络算法及其建模步骤,以及各常用方法的特点。

    And then analyzes several commonly used creek water quality prediction methods , which focused on the BP neural network algorithm and modeling steps . As well as the characteristics of the commonly used method .

  26. 结合理论和实验结果分析,本文发现传统的BP神经网络算法有望在未来物联网体系中突破它的计算瓶颈,赢来快速的发展。

    Combination of theoretical and experimental results , we find that the BP neural network algorithm is expected to break the computational bottleneck in future Internet of Things system , and won its rapid development .

  27. 本文采用模糊神经网络算法对ATM网络进行连接接纳控制,仿真结果表明它比传统的算法有更好的效果。

    This paper brings the fuzzy neural network algorithms into the call admission control in ATM networks . The simulation result shows that it has better effect than usual algorithms .

  28. 结果表明:Hopfield型神经网络算法应用于双运带式输送机主参数的模糊可靠性优化设计十分有效。

    The result shows : it is effective that we apply Hopfield neural network algorithm to the fuzzy reliability optimal design on the main parameter of conveyer .

  29. 为了改善传统方法设计的二维带通三型有限脉冲响应(FIR)滤波器的幅频响应性能,提出了复合正弦基神经网络算法。

    For improving the magnitude and frequency response performance of 2-D bandpass finite impulse response ( FIR ) type-3 filters designed by the conventional algorithms , an compound-sine-basis neural network algorithm was proposed .

  30. 在以上理论学习的基础上,重点是利用最小二乘支持向量机方法对未来河涌水质进行预测,并与BP神经网络算法进行了对比分析。

    On the basis of the above theoretical study . The emphasis is on using the least squares support vector machine to predict the future of the creek water quality . And a comparative analysis and BP neural network algorithm .