Multitask learning deep neural networks to combine revealed and stated preference data

Multitask learning deep neural networks to combine revealed and stated preference data

It is an enduring question how to combine revealed preference (RP) and stated preference (SP) data to analyze individual choices. While the nested logit (NL) model is the classical way to address the question, this study presents multitask learning deep neural networks (MTLDNNs) as an alternative fr...

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Bibliographic Details
Main Authors: Wang, Shenhao, Wang, Qingyi, Zhao, Jinhua
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning
Format: Article
Language:English
Published: Elsevier BV 2020
Online Access:https://hdl.handle.net/1721.1/127228

Internet

https://hdl.handle.net/1721.1/127228

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