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首页> 外文期刊>IEEE journal on electromagnetic compatibility practice and applications >Credibility Evaluation of Electromagnetic Simulation Results Based on Convolutional Neural Network
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Credibility Evaluation of Electromagnetic Simulation Results Based on Convolutional Neural Network

机译:基于卷积神经网络的电磁仿真结果可信度评价

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摘要

The core idea of the credibility evaluation method of electromagnetic simulation results is to replace the experts with an electromagnetic computing professional background to evaluate the credibility of simulation results. The representative algorithm is the feature selective validation (FSV) method proposed by the IEEE Standards Association. However, the existing credibility assessment methods all use statistical indicators or signal processing methods to simulate the real thoughts of experts and have not achieved true artificial intelligence. In this letter, a credibility evaluation method of simulation results based on a convolutional neural network is proposed, which aims to integrate the real ideas of experts (background knowledge of electromagnetic calculation) into the evaluation, instead of just mechanical numerical calculation, and to avoid evaluation errors caused by nonprofessional.
机译:信誉评价方法的核心思想电磁仿真结果用电磁代替专家计算机专业背景来评估仿真结果的可信度。代表性的算法是选择性的特点验证提出的IEEE (FSV)方法标准协会。可信度评估方法都使用统计指标或信号处理方法来模拟专家的真实想法并没有实现真正的人工情报。评价方法的仿真结果的基础上一个卷积神经网络,提出了旨在整合专家的真正想法(电磁的背景知识计算)的评估,而不是力学数值计算,以避免由于非专业评估错误。

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