网络方法

  • 网络Network methods;network approach
网络方法网络方法
  1. RNA二级结构预测的神经网络方法

    Neural network approach to predict RNA secondary structures

  2. 根据平坦瑞利环境下码分多址(CDMA)系统的复信道衰减特点,提出了一种多用户检测的复神经网络方法,从理论上证明了该算法的稳定性。

    A complex neural network approach for implementing optimal multiuser detection in CDMA system is theoretically proposed .

  3. 在BP神经网络方法中,对神经网络的模式和神经网络控制模式进行了系统的学习和应用。

    Study the modeling and control model of BP neural network .

  4. 采用三层BP神经网络方法对冲击地压建立了数学模型。

    A rockburst mathematical model is established by three layers neural network ;

  5. 基于改进BP算法的入侵检测神经网络方法

    The Neural Network Method for Intrusion Detection Based on Improved BP Algorithm

  6. 改进的BP神经网络方法是一种极好的矿业城市循环经济发展的综合评价方法。

    Improved BP artificial neural networks is preferable comprehensive evaluation of circular economy .

  7. 断层推断的改进BP神经网络方法

    Fault recognition by improved BP neural network

  8. 并通过实例证明了方法的可行性,最后与一般的BP神经网络方法进行了对比,体现了该方法的先进性。

    The advantage is shown by contrast with the method of generic BP neural network .

  9. 一种EEG信号盲分离和分类的神经网络方法

    A neural network method of blind separation and classification of EEG signals

  10. 并尝试采用BP神经网络方法对准好氧填埋场的稳定程度进行评价。

    The model based on BP neural network is applied to judge stabilization degree of simi-aerobic landfill .

  11. 最后,通过仿真算例说明BP网络方法用于GPS/SINS组合导航计算的可行性。

    The feasibility of the BP network method applied to the integrated GPS / SINS navigation calculation can be illustrated from a simulation example .

  12. 神经网络方法求解Gabor展开系数

    Computing Gabor Expansion Coefficients by Neural Network

  13. 提出了一种实现DS/CDMA盲多用户检测的改进型Lagrange神经网络方法。

    A algorithm of Blind MUD for realized DS / CDMA has proposed under improved Lagrange neural network .

  14. 利用偏最小二乘法-人工神经网络方法,对富镧Ni-MH电池阴极材料的放电曲线、初始容量、比容量等性能进行研究。

    He PLS BPN method is applied to study the discharge curves , initial capacities and capacity ratios of Ni-MH battery materials .

  15. 观察方向差分约束多副瓣抵消&一种实时处理的Hopfield神经网络方法

    Multi-sidelobe Cancellation of Differential Constrain in Terms of Observing Directions & A Hopfield Neural Network Method of Real Time

  16. 损伤检测方法的发展,包括:(a)动力指纹分析和模式识别方法,(b)模型修正和系统识别方法,(c)神经网络方法;

    Analytical developments of damage detection methods , including ( a ) signature analysis and pattern recognition approaches , ( b ) model updating and system identification approaches , ( c ) neural networks approaches ;

  17. 分析了采煤机的常见故障,介绍了常用的采煤机故障诊断的神经网络方法:BP网络、ART网络和RBF网络。

    The paper analyses coal-raining machine about its common malfunction and introduces usual neural network method of malfunction diagnosis for coal-mining machine : BP network , ART network and RBF network .

  18. 将变压器诊断中典型的油中气体分析法和神经网络方法相结合,采用Java语言开发出界面友好、性能优秀的变压器故障诊断系统;

    Combining ANN with Dissolved Gas Analysis ( DGA ) that is a typical method in transformer diagnosis , transformer fault diagnosis system with friendly interface and excellent capability is finished by Java .

  19. 利用1980~1998年在山东青州调查的数据资料,结合相关气象因子及烟草蚜传病毒病的病情指数,采用BP神经网络方法建立了烟草蚜传病毒病的预测模型。

    Based on data of meteorological factors and tobacco virus diseases transmitted by aphids from 1980 to 1998 in Qingzhou of Shandong province prediction models were established by means of BP neural network .

  20. 小波分析与Kohonen神经网络方法在埋地管道防护层缺陷现场检测中的应用

    Application of wavelet analysis and Kohonen neural networks for fieid detection of spots on underground pipeline coating

  21. 提出了一种改进的BP神经网络方法,它能够解决传统BP神经网络在实际应用中存在的两个问题:收敛速度慢并存在局部极小。

    A new improved back-propagation neural network has been proposed to solve two practical problems encountered by the traditional back-propagation method , i.e. , slow learning progress and convergence to a false local minimum .

  22. 研究表明,应用Hopfield神经网络方法可以得到输气管网布局优化问题的有效解。

    The study shows with the Hopfield neural network method , the effective solution can be achieved for the layout optimization of the gas transmission system .

  23. 结果表明,采用非线性的BP神经网络方法其训练效果与预测效果均优于线性模型方法;

    The accuracy of the model proposed was tested in four compounds , and it was shown that the non-linear model fitted by BP neural network analysis provides much better predictions than the commonly used linear models .

  24. 本文分析了利用油中溶解气体进行变压器故障诊断的方法,对采用IEC三比值法、神经网络方法以及模糊数学方法进行分析。

    In this paper , diagnosis method based on DGA is analyzed . IEC standard , fuzzy theory and expert system are integrated to diagnose the transformer faults .

  25. 其中的人工神经网络方法中的BP网络的实验结果和其它几种预测方法的计算结果相比,BP网络的预测精度高、误差小,在这里充分显示了BP网络在处理非线性问题方面的强大优势。

    The BP network of ANN is the best among these methods comparing from the result . BP network has good precision and lower error , which shows BP network has powerful advantage in dealing with nonlinear problem absolutely .

  26. 用数学模型法研究了细胞间液中Gd()对Ca()物种的影响,并利用人工神经网络方法估算配合物稳定常数。

    The effect of Gd (ⅲ) on Ca (ⅱ) species in human interstitial fluid was studied by mathematical model method . Meantime artificial neural network was applied to the estimation of lg β value of some complex .

  27. 通过对某大桥混凝土腹板裂缝采用非线性BP神经网络方法技术进行综合检测,其结果验证正确,证明了该方法技术的有效性,且较常规的线性方法技术有着更高的精度和可靠性。

    Through adopting nonlinear BP neural network method technology measure synthetically some bridge concrete web cracks , the result is verified correctly . This proves the validity of this method technology which has higher precision and dependability than the routine linear superposition method .

  28. 与现在流行的求取压裂气井无阻流量的方法相比,BP人工神经网络方法具有极大的优越性和适用性,它勿需考虑压裂后气井的复杂渗流规律,也不需数值模拟。

    In comparison with the traditional methods , the BP artificial nerve network method possesses considerable superiority and applicability and it isn 't in need of various steady percolation model based on the percolation theory of gas reservoirs after fracturing or numerical value simulation .

  29. 用该模型对混凝土的强度预测实例表明,其建模速度比标准SVM高近1个数量级,预测误差仅为SVM方法的20%、BP神经网络方法的10%左右。

    The practical experiment results show that the speed of this LS-SVM model is about one order of magnitude higher than SVM model , while the prediction errors are 20 % of SVM model , and about 10 % of BP model .

  30. 研究了求解优化问题全局解的随机神经网络方法,将Gauss模型拓展为广义Gauss模型,使之能求解一般优化问题的全局解。

    The method for global optimization by random artificial neural networks ( AN 2 ) is studied . The Gauss model is modified to an extended Gauss model , which can be used to obtain the global optimum .