规则抽取作为一种形式化的方法来验证和验证神经网络

B. J. Taylor, M.A. Darrah
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引用次数: 36

摘要

术语形式化方法是指在计算机系统和软件的规格说明、设计和构造中使用形式化逻辑和离散数学技术。这些技术使开发和测试的软件形式化,从而可以以更彻底的方式验证和确认。虽然在文献中没有明确地确定为验证和验证(V&V)形式化方法技术,但神经网络规则提取符合基本定义,通过使用形式逻辑的技术来形式化神经网络软件,以便可以更全面地检查它。本文确定了规则提取可以作为神经网络V&V的有效工具的几个领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rule extraction as a formal method for the verification and validation of neural networks
The term formal method refers to the use of techniques from formal logic and discrete math in the specification, design, and construction of computer systems and software. These techniques enable the formalization of software for development and testing so that it may be verified and validated in a more thorough way. Although not specifically identified in the literature as a verification and validation (V&V) formal method technique, neural network rule extraction fits the basic definition by using techniques from formal logic to formalize neural network software so that it may be examined more completely. This paper identifies several areas where rule extraction can be an effective tool for the V&V of neural networks.
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