MATHEMATICAL SUPPORT FOR INDUCTION SOLDERING CONTROL BASED ON INTELLIGENT METHODS OF INFORMATION PROCESSING

А. В. Милов
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引用次数: 0

Abstract

В статье представлены математические модели на основе искусственных нейронных сетей, используемые для управления индукционной пайкой. Обучение искусственных нейронных сетей производилось с использованием многокритериального генетического алгоритма FFGA. This article presents mathematical models based on artificial neural networks used to control induction soldering. The artificial neural networks were trained using the FFGA multicriteria genetic algorithm. The developed models allow to control induction soldering under conditions of incomplete or unreliable information, as well as under conditions of complete absence of information about the technological process.
基于智能信息处理方法的感应焊接控制的数学支持
本文介绍了用于控制感应钎焊的基于人工神经网络的数学模型。使用 FFGA 多标准遗传算法对人工神经网络进行了训练。本文介绍了用于控制感应钎焊的基于人工神经网络的数学模型。使用 FFGA 多标准遗传算法对人工神经网络进行了训练。所开发的模型可以在信息不完整或不可靠的条件下,以及在完全没有技术过程信息的条件下控制感应焊接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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