Application of Machine Learning to Travel Survey Data: Identifying Key Predictors of Health Behaviours

Japanese Journal of Physical Fitness and Sports Medicine ◽

10.7600/jspfsm.71.69_2 ◽

2022 ◽

Vol 71 (1) ◽

pp. 69-69

Author(s):

Manoj Chandrabose

Keyword(s):

Machine Learning ◽

Survey Data ◽

Health Behaviours ◽

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Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach

Traffic and Transportation Studies 2010 ◽

10.1061/41123(383)73 ◽

2010 ◽

Author(s):

Zhongwei Deng ◽

Minhe Ji

Keyword(s):

Machine Learning ◽

Land Use ◽

Survey Data ◽

Learning Approach ◽

Travel Survey ◽

Trip Purpose ◽

Machine Learning Approach

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Corrigendum to “Predicting initial electricity demand in off-grid Tanzanian communities using customer survey data and machine learning models”. [Energy for Sustainable Development 62, 56–66. https://doi.org/10.1016/j.esd.2021.03.008]

Energy for Sustainable Development ◽

10.1016/j.esd.2021.04.007 ◽

2021 ◽

Vol 62 ◽

pp. 175

Author(s):

Andrew Allee ◽

Nathaniel J. Williams ◽

Alexander Davis ◽

Paulina Jaramillo

Keyword(s):

Machine Learning ◽

Sustainable Development ◽

Survey Data ◽

Electricity Demand ◽

Learning Models ◽

Customer Survey ◽

Machine Learning Models

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Analyzing Visitors' Activity Area in Downtown Kumamoto using Smartphone-based Travel-Survey Data

Journal of the City Planning Institute of Japan ◽

10.11361/journalcpij.50.345 ◽

2015 ◽

Vol 50 (3) ◽

pp. 345-351

Author(s):

Takahiro Sato ◽

Takuya Maruyama

Keyword(s):

Survey Data ◽

Travel Survey ◽

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Evaluation Methods for Estimating Vehicle Miles Traveled with GPS Travel Survey Data

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2495-12 ◽

2015 ◽

Vol 2495 (1) ◽

pp. 112-120 ◽

Author(s):

Alejandro Blei ◽

Kazuya Kawamura ◽

Mahmoud Javanmardi ◽

Abolfazl Mohammadian

Keyword(s):

Survey Data ◽

Evaluation Methods ◽

Vehicle Miles Traveled ◽

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Comparing respondent characteristics based on different travel survey data collection and respondent recruitment methods

Case Studies on Transport Policy ◽

10.1016/j.cstp.2020.05.015 ◽

2020 ◽

Vol 8 (3) ◽

pp. 870-877

Author(s):

Ary P. Silvano ◽

Jenny Eriksson ◽

Per Henriksson

Keyword(s):

Data Collection ◽

Survey Data ◽

Recruitment Methods ◽

Travel Survey ◽

Respondent Characteristics

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Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

Transportation ◽

10.1007/s11116-020-10129-5 ◽

2020 ◽

Author(s):

Andrew Bwambale ◽

Charisma F. Choudhury ◽

Stephane Hess ◽

Md. Shahadat Iqbal

Keyword(s):

Mobile Phone ◽

Survey Data ◽

Mobile Phone Data ◽

Trip Generation ◽

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Activity Patterns Identification Based on National Household Travel Survey Data

10.1061/9780784482292.523 ◽

2019 ◽

Author(s):

Chunmiao Wang ◽

Chao Yang ◽

Wen Ye

Keyword(s):

Survey Data ◽

Activity Patterns ◽

Travel Survey ◽

Household Travel Survey ◽

Household Travel ◽

National Household Travel Survey

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Inequalities in self-report road injury risk in Britain: A new analysis of National Travel Survey data, focusing on pedestrian injuries

Journal of Transport & Health ◽

10.1016/j.jth.2018.03.006 ◽

2018 ◽

Vol 9 ◽

pp. 96-104 ◽

Author(s):

Rachel Aldred

Keyword(s):

Survey Data ◽

Injury Risk ◽

Self Report ◽

Travel Survey ◽

Pedestrian Injuries ◽

Road Injury ◽

National Travel Survey

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Using Smartphone Survey Data and Machine Learning to Identify Situational and Contextual Risk Factors for HIV Risk Behavior Among Men Who Have Sex with Men Who Are Not on PrEP

Prevention Science ◽

10.1007/s11121-019-01019-z ◽

2019 ◽

Vol 20 (6) ◽

pp. 904-913 ◽

Author(s):

Tyler B. Wray ◽

Xi Luo ◽

Jun Ke ◽

Ashley E. Pérez ◽

Daniel J. Carr ◽

...

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Risk Behavior ◽

Survey Data ◽

Hiv Risk ◽

Hiv Risk Behavior ◽

Contextual Risk ◽

Sex With Men ◽

Contextual Risk Factors

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Insights from machine learning for evaluating production function estimators on manufacturing survey data

Journal of Productivity Analysis ◽

10.1007/s11123-019-00570-9 ◽

2019 ◽

Vol 53 (2) ◽

pp. 181-225

Author(s):

José Luis Preciado Arreola ◽

Daisuke Yagi ◽

Andrew L. Johnson

Keyword(s):

Machine Learning ◽

Survey Data ◽

Production Function

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