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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Bibliografiska uppgifter
Huvudupphovsmän: Wang, Shenhao, Wang, Qingyi, Zhao, Jinhua
Övriga upphovsmän: Massachusetts Institute of Technology. Department of Urban Studies and Planning
Materialtyp: Artikel
Språk:English
Publicerad: Elsevier BV 2020
Länkar:https://hdl.handle.net/1721.1/127228

Internet

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

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