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Combining evolution strategies and neural network procedures for compression driver design

机译:结合进化策略和神经网络程序进行压缩驱动程序设计

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Compression driver design involves the study of complex mathematical models characterized by a great number of variables, implying high computational cost and long design time. Therefore, an optimization procedure is required to enhance the design procedure, especially from the parameters point of view. In this paper, a combined approach based both on evolution strategy procedure and neural network model is presented. Taking into consideration several tests on a real compression driver, the proposed method is capable to enhance the design procedure from the point of view of obtained frequency response and of the computational performance.
机译:压缩驱动程序设计涉及对复杂数学模型的研究,这些模型具有大量变量,这意味着较高的计算成本和较长的设计时间。因此,需要一种优化程序来增强设计程序,尤其是从参数的角度来看。本文提出了一种基于进化策略过程和神经网络模型的组合方法。考虑到在实际压缩驱动器上的几个测试,从获得的频率响应和计算性能的角度来看,所提出的方法能够增强设计程序。

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