Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Hongcheng Gan"'
Autor:
Huan Lu, Hongcheng Gan
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7921 (2024)
To address the limitations of existing studies on the built environment and commute mode choice, which primarily focus on the objective and residential built environment, this study investigates how commuters’ perceptions of the built environment a
Externí odkaz:
https://doaj.org/article/4c645c5668384135959b2434cdd58624
Publikováno v:
IET Intelligent Transport Systems, Vol 17, Iss 10, Pp 2063-2074 (2023)
Abstract Understanding the impact of smartphone‐based multimodal information (SMMI) on travellers' P&R (park‐and‐ride) choice behaviour is very limited so far. The purpose of this study is to better understand how SMMI, social network informati
Externí odkaz:
https://doaj.org/article/e916b6b1df8e47b999499071f9c4e339
An evolutionary analysis of supply chain collaborative information sharing based on prospect theory.
Publikováno v:
PLoS ONE, Vol 19, Iss 3, p e0298355 (2024)
In order to delve into the dynamic evolution process and influencing factors of information sharing decisions among stakeholders under supply chain collaboration, this study constructs an evolutionary game model with suppliers and retailers as the pr
Externí odkaz:
https://doaj.org/article/27b02740572d4970a68f9af42a49e078
Publikováno v:
European Transport Research Review, Vol 14, Iss 1, Pp 1-19 (2022)
Abstract Summary Gamification is a new theme that has been applied in different fields and has contributed to different types of behavioural change. This paper aims to describe how gamification is adopted in the context of transportation. Methods We
Externí odkaz:
https://doaj.org/article/49508f2442db43f8bdc2e88ad5f9639a
Autor:
Huan Lu, Hongcheng Gan
Publikováno v:
PLoS ONE, Vol 17, Iss 6 (2022)
Background Since December 2019, COVID-19 began to spread throughout the world for nearly two years. During the epidemic, the travel intensity of most urban residents has dropped significantly, and they can only complete inflexible travel such as "hom
Externí odkaz:
https://doaj.org/article/8e9b6062f2bc4372b90b3e58b8e51031
Publikováno v:
Journal of Advanced Transportation, Vol 2022 (2022)
This paper developed a mixed multinomial probit (MMNP) model with alternative error specification and random coefficients (for both generic variables and personal attributes) to accommodate flexible covariance structure and taste variation. The MMNP
Externí odkaz:
https://doaj.org/article/2bc5781c4f0a4b94b482cef03a3bfe1d
Publikováno v:
Environment, Development and Sustainability.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9c8876eb3bcaceff48509eceafd9b3d
https://doi.org/10.1007/s10668-023-03054-x
https://doi.org/10.1007/s10668-023-03054-x
Publikováno v:
Neural Computing and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a832575acb236839de1c663719ec14cd
https://doi.org/10.1007/s00521-022-07756-7
https://doi.org/10.1007/s00521-022-07756-7
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. :036119812311522
In China, a developing country, the car ownership level is much lower than that in developed countries, but transportation policies have been implemented to discourage car ownership and mitigate traffic congestion. However, car ownership (considered
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ff5005e1f93736c4cb28023aad47ae
https://doi.org/10.1177/03611981231152252
https://doi.org/10.1177/03611981231152252
Publikováno v:
Computational intelligence and neuroscience. 2022
It is a critical task to provide recommendation on implicit feedback, and one of the biggest challenges is extreme data sparsity. To tackle the problem, a graph kernel-based link prediction method is proposed in this paper for recommending crowdfundi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::034ca12f17d9b17a0f1a5c63d2a27227
https://pubmed.ncbi.nlm.nih.gov/35909839
https://pubmed.ncbi.nlm.nih.gov/35909839