Delay Prediction of Aircrafts Based on Health Monitoring Data
Published: 2016
Author(s) Name: B. A. Dattaram, N. Madhusudanan |
Author(s) Affiliation: IBM India Pvt Ltd, Bangalore, Karnataka, India
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Abstract
Flight delay is a major issue faced by airline companies. Delay in the aircraft take off can lead to penalty and extra payment to airport authorities leading to revenue loss. The causes for delays can be weather, traffic queues or component issues. In this paper, we focus on the problem of delays due to component issues in the aircraft. In particular, this paper explores the analysis of aircraft delays based on health monitoring
data from the aircraft. This paper analyzes and
establishes the relationship between health monitoring data and the delay of the aircrafts using exploratory analytics, stochastic approaches and machine learning techniques.
Keywords: Aircraft Delay, Faults and Alerts, Markov Chains, Time before Failure, Stochastic Ensemble
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