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Solving nonlinear systems of functional equations with fuzzy adaptive simulated annealing

机译:用模糊自适应模拟退火法求解非线性方程组

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This paper proposes a method for finding solutions of arbitrarily nonlinear systems of functional equations through stochastic global optimization. The original problem (equation solving) is transformed into a global optimization one by synthesizing objective functions whose global minima, if they exist, are also solutions to the original system. The global minimization task is carried out by the stochastic method known as fuzzy adaptive simulated annealing, triggered from different starting points, aiming at finding as many solutions as possible. To demonstrate the efficiency of the proposed method, solutions for several examples of nonlinear systems are presented and compared with results obtained by other approaches. We consider systems composed of n equations on Euclidean spaces R~n (n variables: x_1, x_2, x_3, ..., x_n).
机译:本文提出了一种通过随机全局最优化来寻找函数方程的任意非线性系统解的方法。原始问题(方程求解)通过综合目标函数而转化为全局最优化问题,这些目标函数的全局最小值(如果存在)也是原始系统的解决方案。全局最小化任务通过称为模糊自适应模拟退火的随机方法执行,该方法从不同的起点触发,旨在找到尽可能多的解决方案。为了证明所提方法的有效性,提出了几个非线性系统示例的解决方案,并将其与其他方法获得的结果进行了比较。我们考虑由在欧几里得空间R〜n上的n个方程组成的系统(n个变量:x_1,x_2,x_3,...,x_n)。

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