非线性问题

• To solve the nonlinear problem , such as material nonlinearity and geometrical nonlinearity , incremental method was used
  为解决冲击过程伴随的材料和几何非线性问题，数值分析中采用增量法。
• A kind of linearized algorithm is given out to identify the friction coefficient when the material parameters are known
  进而给出了材料参数已知时，摩擦系数识别非线性问题的一种线性化算法。
• However , it also has two main disadvantages , i . e . , high sensitivity to nonlinear problems and synchronization errors
  但ofdm技术存在着两个主要缺点：对非线性问题敏感，对定时和频率偏移敏感。
• With neural network , non - linear problem can be solved better , as a result , forecasting can accord well with practice even more
  利用神经网络模型可以较好地求解非线性问题，因而使预测结果更符合实际。
• In the other side , since the frost heave is a strongly non - linear problem , the neural networks prediction model is established
  针对冻胀这一强非线性问题，相对于机理模型，建立了路基土冻胀的神经网络预报模型。
• An interesting and fruitful technique for proving existence results for nonlinear problems is the method of upper and lower solutions
  上下解方法和单调迭代技术是研究非线性问题解的存在性的一个有趣而且十分有用的重要工具。
• In this thesis , an incremental - iterative solution procedure using the modified newton - raphson iteration is used to solve geometrically nonlinear problems
  在涉及几何非线性问题的数值方法中，通常都采用增量和迭代分析的方法。
• The non - linear numerical analysis method obtained lays a foundation for the further researching of the mechanical behavior of articaular cartilage
  该非线性问题的数值分析方法，为关节软骨力学行为的深入研究奠定了进一步的基础。
• The kkm principle and equilibrium problem theory are very useful tools for studied various nonlinear problems from natural and social sciences
  Kkm原理和平衡问题理论已成为研究来自自然科学和社会科学中各类非线性问题的有力工具。
• The application of artificial neural networks ( anns ) to predict the ultimate bond strengths of cfrp bonded to concrete is investigated
  摘要碳纤维布与混凝土的极限粘结强度问题属于高度非线性问题，难以建立精确的数学表达式进行分析。