A method to evaluate an aircraft operational risk

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F18%3A00535228" target="_blank" >RIV/60162694:G43__/18:00535228 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.taylorfrancis.com/search?key=9780815386827" target="_blank" >https://www.taylorfrancis.com/search?key=9780815386827</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A method to evaluate an aircraft operational risk

Popis výsledku v původním jazyce

Improving performing and safety of the aircraft operation is one of the most important issues addressed by experts. Such improvement can result not only in the less frequent loss of equipment but primarily in the protection of health or saving lives of both crew members and others involved. Reducing such risks or minimizing impacts is possible by analyzing events, which had already occurred. In this paper, our main motivation consists in developing an effective and intelligent decision support system based on data mining techniques. In this context, data mining classifying algorithms with large datasets have been utilized to assess and analyse the risk factors statistically related to aircraft incidents in order to compare the performance of the implemented classifiers such as decision tree, discriminant and random forest. To nderscore the practical cost, i.e., effectiveness of our approach, the selected classifiers have been implemented using statistical programming tools with datasets taken from the operation process. This analysis is expected to find the algorithm, which can support the decision taking.

Název v anglickém jazyce

A method to evaluate an aircraft operational risk

Popis výsledku anglicky

Improving performing and safety of the aircraft operation is one of the most important issues addressed by experts. Such improvement can result not only in the less frequent loss of equipment but primarily in the protection of health or saving lives of both crew members and others involved. Reducing such risks or minimizing impacts is possible by analyzing events, which had already occurred. In this paper, our main motivation consists in developing an effective and intelligent decision support system based on data mining techniques. In this context, data mining classifying algorithms with large datasets have been utilized to assess and analyse the risk factors statistically related to aircraft incidents in order to compare the performance of the implemented classifiers such as decision tree, discriminant and random forest. To nderscore the practical cost, i.e., effectiveness of our approach, the selected classifiers have been implemented using statistical programming tools with datasets taken from the operation process. This analysis is expected to find the algorithm, which can support the decision taking.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50902 - Social sciences, interdisciplinary

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Safety and Reliability - Safe Societies in a Changing World Proceedings of ESREL 2018, S. Haugen, A. Barros, C. van Gulijk, T. Kongsvik, J. E. Vinnem (editors)

ISBN

9781351174657

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

1441-1446

Název nakladatele

CRC Press

Místo vydání

London

Místo konání akce

Tronheim, Norway

Datum konání akce

17. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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