A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective-Reference-Cited by-同舟云学术

A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective

Published:2021-11-20 Issue: Volume: Page:
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Container-title:2021 The 5th International Conference on Advances in Artificial Intelligence (ICAAI)
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Author:

Bala Bisandu Desmond¹,Salih Homaid Mohammed²,Moulitsas irene²,Filippone Salvatore³

Affiliation:

1. Department of Computational Engineering Sciences, Cranfield University, UK and Machine Learning and Data Analytics Laboratory, Digital Aviation Research and Technology Centre (DARTeC), Cranfield University, UK

2. Department of Computational Engineering Sciences, Cranfield University, UK and Machine Learning and Data Analytics Laboratory, Digital Aviation Research and Technology Centre(DARTeC), Cranfield University, UK

3. Department of Civil and Computer Engineering, Universita di Roma, Italy and Department of Computational Engineering Sciences, Cranfield Univeristy, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3505711.3505712

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5. Aviation Delay Estimation using Deep Learning

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