NDLI: General Diagnostic Framework Based on Non-axiomatic Logic for Aviation Safety Event Analysis

Content Provider	IET Digital Library
Author	G, Yang J I A N G, Hong W A N G, Xingjie F E N
Abstract	To achieve causality reasoning of aviation safety events based on big data of cross-media network, a data-driven general diagnostic framework based on nonaxiomatic logic is designed and implemented. On the basis of this framework, the uncertain causality between aviation safety events and faults is expressed in the form of binary non-axiomatic incident experience at first. A general expression for calculating the attribution and confidence degrees in the non-axiomatic incident experience is given based on records of aviation safety historical incident. A concept of non-axiomatic incident experience graph is proposed, a diagnosis algorithm for aviation safety events is given with the combination of revision and deduction rules in non-axiomatic logic. Experimental results of a Version 1.0 beta demo show that this framework can effectively diagnose all potential faults according to aviation safety events; compared with other machine learning frameworks, it has higher reliability (especially scalability) under the premise of ensuring diagnosis accuracy.
Starting Page	1152
Ending Page	1157
Page Count	6
ISSN	10224653
Volume Number	28
e-ISSN	20755597
Issue Number	Issue 6, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/28/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2019.07.010
Journal	Chinese Journal of Electronics
Publisher Date	2019-11-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Aerospace Computing Aerospace Engineering Computing Aviation Safety Event Analysis Aviation Safety Historical Incident Combinatorial Mathematics Data-driven General Diagnostic Framework Fault Diagnosis Formal Logic Graph Theory Inference Mechanisms Knowledge Engineering Technique Learning in AI Nonaxiomatic Incident Experience Graph Nonaxiomatic Logic
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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