Dynamic Ticket Pricing of Airlines using Variant Batch Size Interpretable Multi-Variable Long Short-Term Memory

Description

Dynamic Ticket Pricing of Airlines using Variant Batch Size Interpretable Multi-Variable Long Short-Term Memory. The proposed model can be used by the airlines to mitigate human judgement on ticket pricing, to manage their price offerings to reach their target revenues and to increase their profits by using observation data as overlapping windows structure.

Steps to reproduce

1. Create a Jupyter Notebook Environment to be able to run a python code 2. Runtime type should be set to GPU 3. Set data path correctly to read from 4. Place the given data file to its location 5. Run the code

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