On Certification of Artificial Intelligence Systems

IF 0.5 4区 物理与天体物理 Q4 PHYSICS, PARTICLES & FIELDS Physics of Particles and Nuclei Pub Date : 2024-06-06 DOI:10.1134/S1063779624030614
D. Namiot, E. Ilyushin
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引用次数: 0

Abstract

Machine learning systems are today the main examples of the use of Artificial Intelligence in a wide variety of areas. From a practical point of view, we can say that machine learning is synonymous with the concept of Artificial Intelligence. The spread of machine learning technologies leads to the need for their application in the so-called critical areas: avionics, nuclear energy, automatic driving, etc. Traditional software, for example, in avionics, undergoes special certification procedures that cannot be directly transferred to machine learning models. The article discusses approaches to the certification of machine learning models.

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关于人工智能系统认证
如今,机器学习系统已成为人工智能广泛应用于各个领域的主要范例。从实用的角度来看,我们可以说机器学习是人工智能概念的同义词。随着机器学习技术的普及,人们需要将其应用于所谓的关键领域:航空电子、核能、自动驾驶等。传统软件,例如航空电子设备中的软件,需要经过特殊的认证程序,而这些程序不能直接应用于机器学习模型。本文讨论了机器学习模型的认证方法。
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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来源期刊
Physics of Particles and Nuclei
Physics of Particles and Nuclei 物理-物理:粒子与场物理
CiteScore
1.00
自引率
0.00%
发文量
116
审稿时长
6-12 weeks
期刊介绍: The journal Fizika Elementarnykh Chastits i Atomnogo Yadr of the Joint Institute for Nuclear Research (JINR, Dubna) was founded by Academician N.N. Bogolyubov in August 1969. The Editors-in-chief of the journal were Academician N.N. Bogolyubov (1970–1992) and Academician A.M. Baldin (1992–2001). Its English translation, Physics of Particles and Nuclei, appears simultaneously with the original Russian-language edition. Published by leading physicists from the JINR member states, as well as by scientists from other countries, review articles in this journal examine problems of elementary particle physics, nuclear physics, condensed matter physics, experimental data processing, accelerators and related instrumentation ecology and radiology.
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