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Application of Powell fruit fly optimization algorithm to solutions of nonlinear equations

机译:鲍威尔果蝇优化算法在非线性方程解的应用中的应用

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Solution to nonlinear equations is with extensive practical meanings in engineering. The convergence of classic numerical solutions is dependent on the initial value which is actually hard to be determined in actual computation. Thus, a new solution to nonlinear equations called PFOA is put forward to turn the complicated solution to nonlinear equations to function optimization. Group search and global convergence of the fruit fly optimization algorithm (FOA) can be fully utilized via PFOA, thereby effectively overcoming the initial point sensitivity of Powell. However, positive local optimal solution can be realized by Powell, so the two algorithms are improved effectively along with integration and complementation in this paper. Five typical nonlinear equations are selected, and the calculation results show the designed PFOA is superior to the basic FOA and is considered a successful solution to nonlinear equations.
机译:非线性方程的解决方案在工程中具有广泛的实用意义。经典数字解决方案的收敛性取决于实际在实际计算中难以确定的初始值。因此,提出了一种名为PFOA的非线性方程的新解决方案,以将复杂的非线性方程转向功能优化。果蝇优化算法(FOA)的集团搜索和全局收敛可以通过PFOA充分利用,从而有效地克服了鲍威尔的初始点敏感性。然而,可以通过Powell实现正本地最佳解决方案,因此两种算法随着本文的集成和互补而有效地提高。选择五个典型的非线性方程,并且计算结果显示设计的PFOA优于基本FOA,并且被认为是非线性方程的成功解决方案。

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