神经网络在安全关键应用中的挑战

H. Forsberg, J. Lindén, J. Hjorth, T. Manefjord, M. Daneshtalab
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引用次数: 7

摘要

在本文中,我们讨论了在安全关键应用中使用神经网络(nn)时面临的挑战。我们着眼于航空安全,逐一应对挑战。然后我们介绍一个可能的实现来克服这些挑战。该解决方案的一小部分已经实际实现,许多工作被认为是未来的工作。我们目前的理解是,在安全关键系统中真正实现将是极其困难的。首先,设计神经网络的预期功能,其次,设计监视器需要实现系统的确定性和故障安全行为。我们得出的结论是,只有最有价值的神经网络实现才应该被认为是有意义的,才能在安全关键系统中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges in Using Neural Networks in Safety-Critical Applications
In this paper, we discuss challenges when using neural networks (NNs) in safety-critical applications. We address the challenges one by one, with aviation safety in mind. We then introduce a possible implementation to overcome the challenges. Only a small portion of the solution has been implemented physically and much work is considered as future work. Our current understanding is that a real implementation in a safety-critical system would be extremely difficult. Firstly, to design the intended function of the NN, and secondly, designing monitors needed to achieve a deterministic and fail-safe behavior of the system. We conclude that only the most valuable implementations of NNs should be considered as meaningful to implement in safety-critical systems.
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