Application of a Genetic Algorithm for Selecting Neural Network Hyperparameters

IF 0.5 Q4 AUTOMATION & CONTROL SYSTEMS

AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2026-02-24 DOI:10.3103/S0146411625700907

V. V. Platonov, A. F. Suprun, Ya. E. Yanbarisova, V. G. Anisimov

引用次数: 0

Abstract

The widespread use of various neural networks (NNs) for detecting network attacks is hampered by the determination of NN hyperparameters. Typically, hyperparameter values are determined experimentally. An approach to select perceptron hyperparameters for detecting network attacks using a genetic algorithm is presented. The experimental results confirm the validity of using this approach.

Abstract Image

查看原文本刊更多论文

遗传算法在神经网络超参数选择中的应用

神经网络超参数的确定阻碍了各种神经网络在网络攻击检测中的广泛应用。通常，超参数值是通过实验确定的。提出了一种利用遗传算法选择感知器超参数来检测网络攻击的方法。实验结果证实了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.70

自引率

22.20%

发文量

期刊介绍： Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision