Abstract
Xiang Liu, Guocong Zhai, Hongtai Yang, Donggen Wang, Mark Zuidgeest, Hongliang Ding, Xiaobo Liu
Abstract
Authors
Institutions
No local reference links have been materialized yet.
No local citing links have been materialized yet.
PyMC: a modern, and comprehensive probabilistic programming framework in Python
10.7717/peerj-cs.1516 · 2023
What would it take for the people of Riyadh city to shift from their cars to the proposed metro?
10.1016/j.cstp.2023.101008 · 2023
Taxicabs as public transportation in boston, massachusetts
10.3141/2277-08 · 2012
Potential distributions of invasive vertebrates in the Iberian Peninsula under projected changes in climate extreme events
10.1111/ddi.13401 · 2021
Travel time estimation in the age of big data
2019
Political economy of infrastructure investment: evidence from the economic stimulus airport grants
10.1016/j.ecotra.2017.12.003 · 2018
Examining the spatial-temporal relationship between urban built environment and taxi ridership: Results of a semi-parametric GWPR model
10.1016/j.jtrangeo.2021.103172 · 2021
A spatiotemporal-guided hybrid learning model for mapping surface air relative humidity
2025
Association between built environment characteristics and metro usage at station level with a big data approach
10.1016/j.tbs.2022.02.007 · 2022
Provenance
crossref
Confidence 100%
ror
Confidence 99%
openalex
Confidence 95%
datacite
Confidence 0%
Fare adjustment’s impacts on travel patterns and farebox revenue: an empirical study based on longitudinal smartcard data
10.1016/j.tra.2022.08.003 · 2022
Effects of proactive and reactive health control measures on public transport preferences of passengers–a stated preference study during the COVID-19 pandemic
10.1016/j.tranpol.2023.11.011 · 2024
Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach
2022
Work-trip mode choice in Germany - Affected by individual constraints or by partner interaction?
10.1016/j.tbs.2021.04.007 · 2021
10.1214/09-aoas285
10.1214/09-aoas285
The indirect effect of the built environment on travel mode choice: A focus on recent movers
10.1016/j.jtrangeo.2021.102983 · 2021
Non-linear relationships between built environment characteristics and electric-bike ownership in Zhongshan, China
10.1016/j.trd.2019.09.005 · 2019
10.1016/j.nhres.2026.06.001
10.1016/j.nhres.2026.06.001
Neglecting spatial autocorrelation causes underestimation of the error of sugarcane yield models
10.1016/j.compag.2018.09.003 · 2019
Beta regression for modelling rates and proportions
10.1080/0266476042000214501 · 2004
Greedy function approximation: a gradient boosting machine
2001
The role of objective and perceived built environments in affecting dockless bike-sharing as a feeder mode choice of metro commuting
10.1016/j.tra.2021.04.008 · 2021
A comparative study of machine learning classifiers for modeling travel mode choice
10.1016/j.eswa.2017.01.057 · 2017
Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model
10.3390/su10061996 · 2018
Multiscale analysis of the influence of street built environment on crime occurrence using street-view images
10.1016/j.compenvurbsys.2022.101865 · 2022
Bayesian additive regression trees: a review and look forward
10.1146/annurev-statistics-031219-041110 · 2020
Causality between multi-scale built environment and rail transit ridership in Beijing and Tokyo
10.1016/j.trd.2024.104150 · 2024
Exploring the Intermodal Relationship between Taxi and Subway in Beijing, China
2018
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
10.1016/j.trd.2022.103426 · 2022
bartMachine: machine learning with bayesian additive regression trees
10.18637/jss.v070.i04 · 2016
What cities have is how people travel: conceptualizing a data-mining-driven modal split framework
10.1016/j.cities.2022.103902 · 2022
Analysis of the relationship between metro ridership and built environment: A machine learning method considering combinational features
10.1016/j.tust.2023.105564 · 2024
Analysis of the relationship between taxi services and public transit in Shanghai: a spatially heterogeneous perspective
2024
The effects of the urban built environment on public transport ridership: similarities and differences
10.1016/j.tbs.2023.100630 · 2023
Understanding the interplay among urban public transport modes: Spatial variation and built environment effects
10.1016/j.jclepro.2024.144038 · 2024
Understanding spatial-temporal travel demand of private and shared e-bikes as a feeder mode of metro stations
10.1016/j.jclepro.2023.136602 · 2023
Analysis of integrated uses of dockless bike sharing and ridesourcing with metros: A case study of Shanghai, China
10.1016/j.scs.2022.103918 · 2022
Research on taxi passenger-finding strategy considering load balancing
2024
An origin-destination level analysis on the competitiveness of bike-sharing to underground using explainable machine learning
10.1016/j.jtrangeo.2023.103716 · 2023
A multiscale spatial analysis of taxi ridership
10.1016/j.jtrangeo.2023.103718 · 2023
Unresolved referenced work
2024
Development of land use regression models to characterise spatial patterns of particulate matter and ozone in urban areas of Lanzhou
10.1016/j.uclim.2024.101879 · doi-reference
Understanding the impact of the built environment on ride-hailing from a spatio-temporal perspective: A fine-scale empirical study from China
10.1016/j.cities.2022.103706 · doi-reference
Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego
10.1016/j.jtrangeo.2022.103449 · doi-reference
Mining Multimodal Travel Mobilities with Big Ridership Data: Comparative Analysis of Subways and Taxis
10.3390/su16104305 · doi-reference
Understanding Taxi Service Strategies From Taxi GPS Traces
10.1109/tits.2014.2328231 · doi-reference
Role of rural built environment in travel mode choice: Evidence from China
10.1016/j.trd.2023.103649 · doi-reference
Exploring the complex relationship between metro and shared bikes in the built environment: competition, connection, and complementation
10.1016/j.scs.2024.105870 · doi-reference
Exploring impacts of the built environment on transit travel: Distance, time and mode choice, for urban villages in Shenzhen, China
10.1016/j.tre.2019.11.004 · doi-reference
Analyzing spatio-temporal distribution pattern and correlation for taxi and metro ridership in Shanghai
10.1007/s12204-019-2051-0 · doi-reference
Gender differences in active travel among older adults: Non-linear built environment insights
10.1016/j.trd.2022.103405 · doi-reference
Does the first/last-mile design matter for transit commuting compared to land use?
10.1016/j.trd.2025.104889 · doi-reference
COVID-19 moderates the association between to-metro and by-metro accessibility and house prices
10.1016/j.trd.2022.103571 · doi-reference
Place-varying impacts of urban rail transit on property prices in shenzhen, china: insights for value capture
10.1016/j.scs.2020.102140 · doi-reference
Exploring the impact of truck traffic on road segment-based severe crash proportion using extensive weigh-in-motion data
10.1016/j.ssci.2023.106261 · doi-reference
Measuring the impact of built environment factors on station-level contributions to link-level crowding using a novel crowding contribution index
10.1038/s41598-025-27483-y · doi-reference
The nonlinear effect of atmospheric conditions on middle-school students’ travel mode choices
10.1016/j.trd.2024.104382 · doi-reference
Shared-use mobility competition: a trip-level analysis of taxi, bikeshare, and transit mode choice in Washington, DC
10.1080/23249935.2018.1523250 · doi-reference
Nonlinear effects of factors on dockless bike-sharing usage considering grid-based spatiotemporal heterogeneity
10.1016/j.trd.2022.103194 · doi-reference
Spatiotemporal analysis of competition between subways and taxis based on multi-source data
10.1109/access.2020.3044956 · doi-reference
New potential for multimodal connection: exploring the relationship between taxi and transit in new york city (NYC)
10.1007/s11116-017-9787-x · doi-reference
Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu
10.1016/j.trd.2021.102776 · doi-reference
The effect of changing registration taxes on electric vehicle adoption in Denmark
10.1016/j.tra.2024.104117 · doi-reference
How does the urban built environment affect dockless bikesharing-metro integration cycling? Analysis from a nonlinear comprehensive perspective
10.1016/j.jclepro.2024.141770 · doi-reference
Promoting public bike-sharing: A lesson from the unsuccessful Pronto system
10.1016/j.trd.2018.06.021 · doi-reference
The impact of fare integration on travel behavior and transit ridership
10.1016/j.tranpol.2012.01.015 · doi-reference
Metro accessibility and space-time flexibility of shopping travel: A propensity score matching analysis
10.1016/j.scs.2022.104204 · doi-reference
Exploring the influence of built environment on uber demand
10.1016/j.trd.2020.102296 · doi-reference
Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco
10.1016/j.tranpol.2015.10.004 · doi-reference
Using ensembles of decision trees to predict transport mode choice decisions: effects on predictive success and uncertainty estimates
10.18757/ejtir.2014.14.4.3045 · doi-reference
Parallel Bayesian additive regression trees
10.1080/10618600.2013.841584 · doi-reference
Statistical comparison of additive regression tree methods on ecological grassland data
10.1016/j.ecoinf.2020.101198 · doi-reference
Evaluating the household-level climate-electricity nexus across three cities through statistical learning techniques
10.1016/j.seps.2023.101664 · doi-reference
Examining ride sourcing services as an emerging mode in Metro Vancouver: Insights into trip characteristics and impacts on multimodal competitions
10.1080/15568318.2024.2363203 · doi-reference
Economic and distributional effects of different fare schemes: evidence from the metropolitan region of barcelona
10.1016/j.tra.2020.05.014 · doi-reference
A multiscale spatial analysis of taxi ridership
10.1016/j.jtrangeo.2023.103718 · doi-reference
An origin-destination level analysis on the competitiveness of bike-sharing to underground using explainable machine learning
10.1016/j.jtrangeo.2023.103716 · doi-reference
Analysis of integrated uses of dockless bike sharing and ridesourcing with metros: A case study of Shanghai, China
10.1016/j.scs.2022.103918 · doi-reference
Understanding spatial-temporal travel demand of private and shared e-bikes as a feeder mode of metro stations
10.1016/j.jclepro.2023.136602 · doi-reference
Understanding the interplay among urban public transport modes: Spatial variation and built environment effects
10.1016/j.jclepro.2024.144038 · doi-reference
The effects of the urban built environment on public transport ridership: similarities and differences
10.1016/j.tbs.2023.100630 · doi-reference