基于偏微分的非线性代数方程组并行模型设计

Design of partial differentiation based parallel model of nonlinear algebraic equation set

目前提出的非线性代数方程组并行模型运算成功率较低,导致其搜索速度较慢。为了解决上述问题,设计了基于偏微分的非线性代数方程组并行模型。该模型的设计核心是引入偏微分算法调用传统的非线性代数方程组,从而构建非线性代数方程并行算法;然后在去噪处理的基础上,建立数据通道,通过数据通道筛选问题数据,利用迭代算法实现并行运行,从而得到最终基于偏微分的非线性代数方程组的并行模型。实验结果表明,设计的模型能够有效提高运算成功率,加快搜索速度。

At present,the parallel model of nonlinear algebraic equations has low success rate of operation,which leads to slow search speed.For this reason,a partial differential based parallel model of nonlinear algebraic equations is designed.The design core of the model is to introduce the partial differential algorithm to call the traditional nonlinear algebraic equation set,so as to construct a parallel algorithm of nonlinear algebraic equation set.Then,on the basis of denoising processing,a data channel is established to screen the problem data.The iterative algorithm is used to realize parallel operation,so as to obtain the partial differential based final parallel model of nonlinear algebraic equation set.The experimental results show that the model designed in this study can effectively increase the success rate of operation and speed up the search speed.