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An Evolutionary Approach for Approximating the Solutions of Systems of Linear Fuzzy Equations

机译:逼近线性模糊方程组解的进化方法

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In this paper systems of linear equations Ax = b, where both A and b contain uncertain factors in terms of fuzziness are investigated. The classical solutions being vectors of fuzzy numbers are considered. The complex problem of finding the exact classical solutions is replaced by a corresponding optimization task with the cost function based on the Hausdorff metric. This cost function is next minimized with use of genetic algorithms. A number of numerical experiments are provided in order to verify the given approach. The results and some conclusions are also included.
机译:在本文中,线性方程组Ax = b的系统,其中A和b都包含模糊性方面的不确定因素。考虑经典解是模糊数的向量。寻找精确经典解的复杂问题被具有基于Hausdorff度量的成本函数的相应优化任务所代替。接下来,使用遗传算法将成本函数最小化。为了验证给定的方法,提供了许多数值实验。结果和一些结论也包括在内。

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