非线性问题

• The deformation and vibration analysis of cables under common loads is therefore a complex nonlinear problem as geometric non - linearity is generally involved
  因此悬索在一般荷载下的变形和振动问题便是一个较为复杂的几何非线性问题。
• The algorithm give over vice of the simple back propagation algorithm ( sbp ) that plunge the part extremes in some intricate nonlinear problems
  同时，针对sbp神经网络对于复杂的非线性问题容易陷入局部极值，提出了改进的bp算法( nfcs - caf ) 。
• The inverse operator method has much advantage , such as high degree of accuracy , little limit ability to solve strong nonlinear problem and so on
  该方法具有精度高、限制少、能够解决强非线性问题等优点。本文还建立了一类普朗特边界层问题的数学模型。
• The contact problems are non - linear problems , which relate to stress concentration , local boundary nonlinear , no - reversibility of shear force , and so on
  接触问题是非线性问题，涉及到应力集中、局部边界非线性、切向力的不可逆性等一系列非线性问题。
• The simulation and practice showed that the bp neural network was an effective and convenient measure to solve the complicate and nonlinear project
  预测结果表明，神经网络方法建模简单，精度高，对于企业风险等复杂的非线性问题有着很强的逼近与预测能力。
• Furthermore , a method that can realize quasi - constant envelope modulation merely by the change of the coding scheme are proposed to unbend the nonlinear effects in amplifiers
  为了缓解功放的非线性问题,还提出并推导了一种从编码角度来实现准恒幅调制的方法。
• Examples show that the element free galerkin method still possesses some advantages such as good stability and high rate of convergence in solving geometrically nonlinear problems
  算例表明，在用无单元迦辽金法求解几何非线性问题时仍具有稳定性好、收敛快等优点。
• Such correction reduces the input range , the condition of linear system is fulfilled and linear correction on corresponding pixel is effective in this range
  该方法通过缩小校正的输入范围，满足线性系统成立的条件，使非线性问题线性化，实现了各像元点对点的线性校正。
• The genetic algorithm was applied to solute nonlinear constraint optimization problems . the optimum solution was explained in determine the nature from the craft ' s angle
  采用遗传算法对以带约束优化的非线性问题进行了求解，并从工艺的角度对优化的结果进行定性的解释。
• Non - linear classification in many research fields is very difficult . so not only good classified decision but also good method of feature extraction need to be studied
  非线性问题是很多学科研究当中经常遇到的困难,不仅要研究较好分类决策,而且要研究较好的特征提取方法。