Combining discrete choice models and neural networks through embeddings: Formulation, interpretability and performance-Reference-Cited by-同舟云学术

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Combining discrete choice models and neural networks through embeddings: Formulation, interpretability and performance

Published:2023-09 Issue: Volume:175 Page:102783
ISSN:0191-2615
Container-title:Transportation Research Part B: Methodological
language:en
Short-container-title:Transportation Research Part B: Methodological

Author:

Arkoudi Ioanna^ORCID,Krueger Rico,Azevedo Carlos Lima,Pereira Francisco C.^ORCID

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Transportation,Civil and Structural Engineering

Reference55 articles.

1. Regularized categorical embedding for effective demand forecasting of bike sharing system;Ahn,2021

2. Multi-task feature learning;Argyriou,2007

3. Opening up the conversation: Topic modeling for automated text analysis in travel surveys;Baburajan,2018

4. Rand corporation;Bellman;Dynamic Programming,1957

5. Hybrid choice models: Progress and challenges;Ben-Akiva;Mark. Lett.,2002

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2. Modeling travel mode choice behavior for planned special events using CPT-based HI-MADM approach;Transportation Letters;2024-05-16

3. A new flexible and partially monotonic discrete choice model;Transportation Research Part B: Methodological;2024-05

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