Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
Deep neural networks for choice analysis: Extracting complete economic information for interpretation
While deep neural networks (DNNs) have been increasingly applied to choice analysis
showing high predictive power, it is unclear to what extent researchers can interpret …
showing high predictive power, it is unclear to what extent researchers can interpret …
Machine learning for activity pattern detection
NS Hadjidimitriou, G Cantelmo… - Journal of Intelligent …, 2023 - Taylor & Francis
This paper proposes a data fusion approach to automatically detect activity patterns in a
GPS dataset based on travel diaries and correct misclassification errors. The Activity …
GPS dataset based on travel diaries and correct misclassification errors. The Activity …
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
Researchers often treat data-driven and theory-driven models as two disparate or even
conflicting methods in travel behavior analysis. However, the two methods are highly …
conflicting methods in travel behavior analysis. However, the two methods are highly …
Insights on data quality from a large-scale application of smartphone-based travel survey technology in the Phoenix metropolitan area, Arizona, USA
Collecting accurate travel data is vital for transportation planning purposes. Regional travel
demand forecasts as well as transportation system analyses depend on datasets that …
demand forecasts as well as transportation system analyses depend on datasets that …
Exploring strengths and weaknesses of mobility inference from mobile phone data vs. travel surveys
N Caceres, LM Romero, FG Benitez - … A: Transport Science, 2020 - Taylor & Francis
Origin–destination (OD) matrices serve as a basis for travel demand modelling. Traditionally,
they are derived from travel surveys that collect detailed trip information but with several …
they are derived from travel surveys that collect detailed trip information but with several …
IoT-based healthcare system for real-time maternal stress monitoring
There is a major concern about pregnancy-associated stress and anxiety, which are key risk
factors for various pregnancy complications involving the health of mother and fetus [13, 14 …
factors for various pregnancy complications involving the health of mother and fetus [13, 14 …
Incorporating multiple congestion levels into spatiotemporal analysis for the impact of a traffic incident
Traffic incidents occurring on the road interrupt the smooth mobility of traffic flow and lead to
traffic congestion. Although there has been a proliferation of studies that attempt to estimate …
traffic congestion. Although there has been a proliferation of studies that attempt to estimate …
A combined solution for real-time travel mode detection and trip purpose prediction
Identifying the travel modes people use on their daily commute, and the purpose of their
trips, contributes to a better understanding of their mobility patterns. Therefore, the detection …
trips, contributes to a better understanding of their mobility patterns. Therefore, the detection …
Visualizing, clustering, and characterizing activity-trip sequences via weighted sequence alignment and functional data analysis
Smartphone-based activity-travel surveys have enabled the collection of continuous, multi-
day data on individuals' trips and activities with high spatial and temporal resolution …
day data on individuals' trips and activities with high spatial and temporal resolution …