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Mengnan Du et al.
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Xiaoyi Zhou et al.
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Zhiyong Cui et al.
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Threshold and moderating effects of land use on metro ridership in Shenzhen: Implications for TOD planning
Qifan Shao et al.
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Taehooie Kim et al.
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Xilei Zhao et al.
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Machine learning applications in activity-travel behaviour research: a review
Anil N. P. Koushik et al.
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Using machine learning for direct demand modeling of ridesourcing services in Chicago
Xiang Yan et al.
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DeepPF: A deep learning based architecture for metro passenger flow prediction
Yang Liu et al.
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Qin Zhang et al.
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Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning
Xiaolu Zhou et al.
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Sizing up transport poverty: A national scale accounting of low-income households suffering from inaccessibility in Canada, and what to do about it
Jeff Allen et al.
TRANSPORT POLICY (2019)
Applying a random forest method approach to model travel mode choice behavior
Long Cheng et al.
TRAVEL BEHAVIOUR AND SOCIETY (2019)
Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists
Avipsa Roy et al.
URBAN SCIENCE (2019)
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Cynthia Rudin
NATURE MACHINE INTELLIGENCE (2019)
Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model
Fangru Wang et al.
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Comparison of Four Types of Artificial Neural Network and a Multinomial Logit Model for Travel Mode Choice Modeling
Dongwoo Lee et al.
TRANSPORTATION RESEARCH RECORD (2018)
The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models
Julian Koch et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2018)
Gender gap generators for bicycle mode choice in Baltimore college campuses
Farhad Abasahl et al.
TRAVEL BEHAVIOUR AND SOCIETY (2018)
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model
Mehmet C. Demirel et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2018)
A spatio-temporal accessibility measure for modelling activity participation in discretionary activities
Koos Fransen et al.
TRAVEL BEHAVIOUR AND SOCIETY (2018)
Elderly travel frequencies and transport mode choices in Greater Rotterdam, the Netherlands
Lars Bocker et al.
TRANSPORTATION (2017)
A comparative study of machine learning classifiers for modeling travel mode choice
Julian Hagenauer et al.
EXPERT SYSTEMS WITH APPLICATIONS (2017)
Transit accessibility, land development and socioeconomic priority: A typology of planned station catchment areas in the Greater Toronto and Hamilton Area
Steven Farber et al.
JOURNAL OF TRANSPORT AND LAND USE (2017)
A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting
Pinlong Cai et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2016)
Travelling fair: Targeting equitable transit by understanding job location, sectorial concentration, and transit use among low-wage workers
Alexander Legrain et al.
JOURNAL OF TRANSPORT GEOGRAPHY (2016)
Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
Alex Goldstein et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2015)
The effects of high-density suburban development on commuter mode choices in Seoul, Korea
Myung-Jin Jun et al.
CITIES (2013)
Explaining transport mode use of low-income persons for journey to work in urban areas: a case study of Ontario and Quebec
Ruben G. Mercado et al.
TRANSPORTMETRICA (2012)
Accessibility to transit, by transit, and mode share: application of a logistic model with spatial filters
Md Moniruzzaman et al.
JOURNAL OF TRANSPORT GEOGRAPHY (2012)
Zero-Inflated and Hurdle Models of Count Data with Extra Zeros: Examples from an HIV-Risk Reduction Intervention Trial
Mei-Chen Hu et al.
AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE (2011)
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
Joaquin Derrac et al.
SWARM AND EVOLUTIONARY COMPUTATION (2011)
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
Salvador Garcia et al.
INFORMATION SCIENCES (2010)
Travel and the Built Environment
Reid Ewing et al.
JOURNAL OF THE AMERICAN PLANNING ASSOCIATION (2010)
Residential choice, the built environment, and nonwork travel: evidence using new data and methods
Daniel G. Chatman
ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE (2009)
Travel Mode Choice Modeling with Support Vector Machines
Yunlong Zhang et al.
TRANSPORTATION RESEARCH RECORD (2008)
Urban form and travel behaviour: Micro-level household attributes and residential context
FM Dieleman et al.
URBAN STUDIES (2002)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)
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