基于AF-PSO求解缓和曲线非线性方程组

在线路测设工程中,根据缓和曲线内外侧地面点的实测坐标,推导出曲线非线性方程,解算出对应的曲线长具有一定的实际意义。针对传统牛顿迭代解法计算量大,对形式复杂方程不适用等问题,提出一种基于人工鱼群和粒子群的协同优化算法,该算法综合利用人工鱼群算法的良好全局收敛性和粒子群算法的局部快速收敛性、易实现性等优点,发挥两者的优越性。实例表明,人工鱼群和粒子群协同优化算法可以很好地应用到缓和曲线非线性方程组的求解中,且收敛速度快,求解精度高。

Hybrid optimization algorithm based on artificial fish swarm and particle swarm algorithm

During the works of line surverying ,it’s of great significance to derive the nonlinear equations and solve the length of curvve according to the measured coordinate of ground point of the relaxation curve .But the traditional New ton solution has a large amount of calculation and can ’t be used to solve the complex equations .The hybrid optimization algorithm based on artificial fish swarm and particle swarm algorithm is better than the traditional New ton solution ,w hich makes full use of the fast convergence of AFSA and the global convergence of PSO .It combines the advantages of both .The examples show it can be used to solve the nonlinear equations of transition curve .