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为了解决区域交通活动场模拟分析过程中的稀疏矩阵求解问题,本文针对自适应交通网络模型中的稀疏矩阵的特性,提出了两种稀疏矩阵处理技术。采用基于矩阵分裂的超松弛迭代法和以共轭向量系为搜索方向的共轭梯度法,使得模型中的稀疏矩阵求解问题顺利解决。经过计算得到,在得到同样精度的结果时,两种算法的收敛速度是不一样的,共轭梯度法有着明显的优势。
In order to solve the problem of sparse matrix in the process of simulation analysis of regional traffic field, this paper proposes two sparse matrix processing techniques for the characteristics of sparse matrix in adaptive traffic network model. Using the over-relaxation iterative method based on matrix splitting and the conjugate gradient method with the conjugate vector system as the search direction, the sparse matrix solution problem in the model is solved smoothly. After calculation, when the same precision result is obtained, the convergence speed of the two algorithms is not the same, and the conjugate gradient method has obvious advantages.