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An intelligent computing technique to estimate the magnetic field generated by overhead transmission lines using a hybrid GA-Sx algorithm

机译:使用混合GA-Sx算法估算架空输电线路产生的磁场的智能计算技术

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摘要

The application of certain Artificial Intelligence techniques provides an efficient solution to the problem of characterizing the magnetic field of a high voltage overhead transmission line, and is an alternative to the expensive procedure of direct measurements, which requires equipment and time, to the use of complex numerical methods of a very specific scope, or of simply obtaining a theoretical value calculated using analytical procedures which forego the quality of the solution in favor of simplifying the calculations. This paper presents an implementation based on a hybrid algorithm in which the best solutions provided by a metaheuristics (a genetic algorithm which allows working with extensions) define the initial simplex for the application of the Nelder-Mead Method, which as a local search method permits a calculation-intensive search. In order to validate the quality of the results generated by this hybrid implementation, the estimates obtained are compared with measured values and with values obtained by means of analytical procedures.
机译:某些人工智能技术的应用为表征高压架空传输线的磁场问题提供了有效的解决方案,并且是昂贵的直接测量过程的替代方法,该过程需要设备和时间,而且要使用复杂的仪器非常具体的范围内的数值方法,或者只是获得使用分析程序计算的理论值,这些分析程序放弃了解决方案的质量,而是简化了计算。本文提出了一种基于混合算法的实现,其中由元启发式算法(一种允许与扩展一起使用的遗传算法)提供的最佳解决方案定义了适用于Nelder-Mead方法应用的初始单纯形,作为局部搜索方法,它可以计算密集型搜索。为了验证通过此混合实施生成的结果的质量,将获得的估计值与测量值以及通过分析程序获得的值进行比较。

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