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Original paper

Flight delay prediction for commercial air transport: A deep learning approach

Volume: 125, Pages: 203 - 221
Published: Mar 20, 2019
Abstract
This study analyzes high-dimensional data from Beijing International Airport and presents a practical flight delay prediction model. Following a multifactor approach, a novel deep belief network method is employed to mine the inner patterns of flight delays. Support vector regression is embedded in the developed model to perform a supervised fine-tuning within the presented predictive architecture. The proposed method has proven to be highly...
Paper Details
Title
Flight delay prediction for commercial air transport: A deep learning approach
Published Date
Mar 20, 2019
Volume
125
Pages
203 - 221
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