Are first responders prepared for electric vehicle fires? A national survey
Transitioning to electric vehicles (EVs) will create both opportunities and challenges.
Although some programs and resources related to EVs have been made available to first …
Although some programs and resources related to EVs have been made available to first …
Associating incident clearance duration with freeway segment types using hierarchical Bayesian survival model
Traffic incidents represent nonrecurring events that have long been found to deteriorate
traffic operations and safety. Studies agree that quick incident clearance would translate into …
traffic operations and safety. Studies agree that quick incident clearance would translate into …
A spatial autoregressive geographically weighted quantile regression to explore housing rent determinants in Amsterdam and Warsaw
A hedonic approach is typically performed to identify housing rental or sales price
determinants. However, standard hedonic regression models disregard spatial …
determinants. However, standard hedonic regression models disregard spatial …
A Two‐Stage Sequential Framework for Traffic Accident Post‐Impact Prediction Utilizing Real‐Time Traffic, Weather, and Accident Data
A Abdi, S Seyedabrishami… - Journal of advanced …, 2023 - Wiley Online Library
Detecting road accident impacts as promptly as possible is essential for intelligent traffic
management systems. This paper presents a sequential two‐stage framework for predicting …
management systems. This paper presents a sequential two‐stage framework for predicting …
Automatic Accident Detection, Segmentation and Duration Prediction Using Machine Learning
Traffic accidents are often inaccurately reported, with incorrect location and disruption
duration due to various external factors. This can result in imprecise predictions and …
duration due to various external factors. This can result in imprecise predictions and …
Factorial design–machine learning approach for predicting incident durations
This research proposes a hybrid approach for predicting incident duration that integrates the
salient features of both factorial design of experiments (DOE) and machine learning (ML) …
salient features of both factorial design of experiments (DOE) and machine learning (ML) …
Analyzing freeway traffic incident clearance time using a deep survival model
Accurately predicting freeway incident clearance time and analyzing influential factors are
essential for developing effective traffic incident management strategies. Existing …
essential for developing effective traffic incident management strategies. Existing …
Comprehensive evaluation of multiple machine learning classifiers for predicting freeway incident duration
This study compares the accuracy and complexity of eleven machine learning classifiers for
the problem of incident duration prediction. The proposed framework integrates feature …
the problem of incident duration prediction. The proposed framework integrates feature …
Quantile regression-based prediction of intraoperative blood loss in patients with spinal metastases: model development and validation
J Li, J Zhang, X Zhang, D Lun, R Li, R Ma, Y Hu - European Spine Journal, 2023 - Springer
Purpose To develop and evaluate a quantile regression-based blood loss prediction model
for open surgery of spinal metastases. Methods This was a multicenter retrospective cohort …
for open surgery of spinal metastases. Methods This was a multicenter retrospective cohort …
LaTeX: Language Pattern-aware Triggering Event Detection for Adverse Experience during Pandemics
The COVID-19 pandemic has accentuated socioeconomic disparities across various racial
and ethnic groups in the United States. While previous studies have utilized traditional …
and ethnic groups in the United States. While previous studies have utilized traditional …