信任机器学习在航空领域的应用

K. Benmeziane, P. Fabiani, S. Herbin, J. Lacaille, E. Ledinot
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引用次数: 0

摘要

法国航空航天标准化办公室(BNAE)正在起草一份总体建议,由奥涅拉、泰雷兹、达索和赛峰集团的专家在法国主要航空公司空中客车、MBDA和ADP的合作下起草。考虑到基于从数据集或数据生成器学习方法的算法的特殊性,本文档基于在系统和软件开发过程中重新引入的数学和统计元素。对于这一开发过程中的每一项活动,无论是数据资本化还是人工智能的使用,都确定了风险,并提出了缓解方法。文档中包含了一些应用案例,以说明某些类型算法的特殊性。提到了估计、分类、分类甚至强化学习的方法。本文用英文概述了一般性建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trusting Machine-Learning Applications in Aeronautics
A general recommendation from the French office for aeronautical and space standardization (BNAE) is being drawn up by experts from Onera, Thales, Dassault and Safran, with the collaboration of Airbus, MBDA and ADP, the main French aeronautical companies. This document is based on mathematical and statistical elements which are reintroduced within a system and software development process considering the specificities of algorithms based on learning methods from data sets or data generators. For each activity in this development process, whether it is data capitalization or the use of artificial intelligence, risks are identified, and mitigation methods proposed. A few application cases are included in the document to illustrate the particularities of certain types of algorithms. Methods of estimation, classification, categorization or even reinforcement learning are mentioned. This paper gives a summary in English of the general recommendation.
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