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ARTIFICIAL INTELLIGENCE AND CYBERSECURITY, UNIVERSITY KLAGENFURT
参考中译:克拉根福大学人工智能与网络安全


          

刊名：Electronic Device Failure Analysis
作者：Konstantin Schekotihin（University Klagenfurt）
刊号：770B0007
ISSN：1537-0755
出版年：2023
年卷期：2023, vol.25, no.2
页码：33
总页数：1
分类号：TN60
语种：eng
文摘：The department of Artificial Intelligence and Cyber-security (AI&CS), University Klagenfurt, Austria, focuses on research and application of AI methods to various practical problems. Many of our activities are conducted within research projects with industrial partners, where logic-based methods are combined with machine learning to solve complex problems related to the digitalization of business processes. In the failure analysis (FA) domain, our activities aim to develop an intelligent FA assistant that can automate many tedious and routine, but nevertheless essential activities, helping an FA engineer to localize physical failures as efficiently as possible. Therefore, the assistant's main task is to predict the possible failure using information collected by the FA engineer so far and recommend the most probable hypothesis. This task requires an application of both symbolic and machine-learning methods. The former are used to collect and store knowledge from FA engineers about the domain in a machine-readable form, whereas the latter combine this knowledge with raw data resulting in the application of FA methods.
参考中译：奥地利克拉根福大学人工智能与网络安全(AI&CS)系专注于人工智能方法的研究和应用于各种实际问题。我们的许多活动都是在与行业合作伙伴的研究项目中进行的，在这些项目中，基于逻辑的方法与机器学习相结合，以解决与业务流程数字化相关的复杂问题。在故障分析(FA)领域，我们的活动旨在开发一种智能FA助手，该助手可以自动执行许多乏味和常规但仍然必不可少的活动，帮助FA工程师尽可能有效地定位物理故障。因此，S助理的主要任务是利用FA工程师到目前为止收集的信息来预测可能的故障，并推荐最可能的假设。这项任务需要应用符号和机器学习方法。前者用于收集和存储FA工程师关于该领域的机器可读形式的知识，而后者将这些知识与原始数据相结合，从而导致FA方法的应用。



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