论文标题
曲线/曲线相交的自适应迭代/细分混合算法
An adaptive iterative/subdivision hybrid algorithm for curve/curve intersection
论文作者
论文摘要
[20]中提出的曲线/曲线相交的迭代/细分混合算法的行为取决于其收敛测试的域选择。使用太小或太大的测试域可能会导致测试未能检测到牛顿方法实际上会收敛到解决方案的情况，从而导致不必要的其他细分，因此增加了计算时间。我们建议对算法进行修改，以根据母体区域测试过程中发生的情况自适应地调节测试域的大小。这与原始算法相反，其测试域始终是所考虑的输入域的固定倍数。计算结果表明，所提出的算法比原始算法略有效率。
The behavior of the iterative/subdivision hybrid algorithm for curve/curve intersection proposed in [20] depends on the choice of the domain for their convergence test. Using either too small or too large test domain may cause the test to fail to detect cases where Newton's method in fact converges to a solution, which results in unnecessary additional subdivisions and consequently more computation time. We propose a modification to the algorithm to adaptively adjust the test domain size according to what happens during the test of the parent region. This is in contrast to the original algorithm whose test domain is always a fixed multiple of the input domain under consideration. Computational results show that the proposed algorithm is slightly more efficient than the original algorithm.
