Learning From Accidents: Machine Learning for Safety at Railway Stations
نویسندگان
چکیده
منابع مشابه
Learning from Normal Accidents
can be found at: Organization & Environment Additional services and information for http://oae.sagepub.com/cgi/alerts Email Alerts: http://oae.sagepub.com/subscriptions Subscriptions: http://www.sagepub.com/journalsReprints.nav Reprints: http://www.sagepub.com/journalsPermissions.nav Permissions: http://oae.sagepub.com/cgi/content/refs/17/1/15 SAGE Journals Online and HighWire Press platforms...
متن کاملApplication of Machine Learning Techniques for Railway Health Monitoring
Emerging wireless sensor networking (WSN) and modern machine learning techniques have encouraged interest in the development of vehicle health monitoring (VHM) systems that ensure secure and reliable operation of the rail vehicle. The performance of rail vehicles running on railway tracks is governed by the dynamic behaviours of railway bogies especially in the cases of lateral instability and ...
متن کاملTechnological Accidents: Learning from Disaster
Financial support from the program " Risques collectifs et situations de crise " of CNRS is gratefully acknowledged. In 1979 a partial melt-down of the reactor core at Three Mile Island was the worst nuclear power accident to that time. massive radiation overdoses during treatment using the Therac-25 machine. In the summer of 1991, ten million subscribers in the United States lost telephone ser...
متن کاملCapacity utilisation and performance at railway stations
As traffic levels increase on railways in Britain and elsewhere, improved understanding of the trade-offs between capacity provision/utilisation and service quality is increasingly important, as Infrastructure Managers and Railway Undertakings seek to maximise capacity provision without an unacceptable loss of service reliability and punctuality. This is particularly true of the stations and ju...
متن کاملKnowledge Based System for the Evaluation of Safety and the Prevention of Railway Accidents
This paper describes a contribution to improving the usual safety analysis methods used in the certification of railway transport systems. The methodology is based on the complementary and simultaneous use of knowledge acquisition and machine learning. The purpose is contributed to the generation of new accident scenarios that could help experts to conclude on the safe character of a new rail t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2019.2962072