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Fuzzy-Genetic Algorithm for Pre-Processing Data at the RTU

机译:RTU数据预处理的模糊遗传算法

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摘要

Uncertainties are always present in the data captured at the remote terminal unit (RTU) in a power system. In this paper, it has been demonstrated that pre-processing the data with a fuzzy-genetic algorithm at the RTU will reduce the uncertainty and vagueness in the measurands. The initial population for the genetic algorithm is generated with assumed fuzzy functions. These functions are optimized using the theory of reproduction, cross over and mutation. The result shows that the fuzzy-genetic algorithm gives better results than the other methods available. It is also observed that the fuzzy-genetic algorithm is easy to apply to the output fuzzy solution rather than to the input fuzzy function.
机译:电力系统中远程终端单元(RTU)捕获的数据中始终存在不确定性。在本文中,已经证明了在RTU上使用模糊遗传算法对数据进行预处理将减少被测对象的不确定性和模糊性。遗传算法的初始种群是通过假定的模糊函数生成的。这些功能使用繁殖,交叉和变异理论进行了优化。结果表明,模糊遗传算法比其他可用方法具有更好的结果。还观察到,模糊遗传算法易于应用于输出模糊解,而不是应用于输入模糊函数。

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