Dynamic ticket pricing of airlines using variant batch size interpretable multi-variable long short-term memory

作者：

Highlights：

• Dynamic Airline Ticket Pricing based on Machine Learning algorithms.

• Reduce human judgement by training models with the best sales performance data.

• Price estimation by also considering based on cost and revenue attributes.

• Using a dynamic batch size consisting of non-sequential data to feed the model.

摘要

•Dynamic Airline Ticket Pricing based on Machine Learning algorithms.•Reduce human judgement by training models with the best sales performance data.•Price estimation by also considering based on cost and revenue attributes.•Using a dynamic batch size consisting of non-sequential data to feed the model.

论文关键词：Air Transportation,Dynamic Ticket Pricing,Neural Networks,Deep learning,Long short term memory,Forecasting

论文评审过程：Received 29 June 2020, Revised 24 February 2021, Accepted 24 February 2021, Available online 3 March 2021, Version of Record 1 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114794