[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and developing effective road safety …
are a prerequisite for devising countermeasures and developing effective road safety …
Crash data augmentation using variational autoencoder
In this paper, we present a data augmentation technique to reproduce crash data. The
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
[PDF][PDF] Data mining based marketing decision support system using hybrid machine learning algorithm
TS Kumar - Journal of Artificial Intelligence, 2020 - engineersplanet.com
Data mining is widely used in engineering and science, On the contrary, it is used in finance
and marketing applications to resolve the challenges in the respective fields. Data mining …
and marketing applications to resolve the challenges in the respective fields. Data mining …
A Long Short-Term Memory-based correlated traffic data prediction framework
Correlated traffic data refers to a collection of time series recorded simultaneously in
different regions throughout the same transportation network route. Due to the presence of …
different regions throughout the same transportation network route. Due to the presence of …
Interpretable data science for decision making
K Coussement, DF Benoit - Decision Support Systems, 2021 - Elsevier
This paper describes the foundations of interpretable data science for decision making and
serves as an editorial to the corresponding special issue. Interpretable data science …
serves as an editorial to the corresponding special issue. Interpretable data science …
Spatiotemporal instability analysis considering unobserved heterogeneity of crash-injury severities in adverse weather
Adverse weather could potentially increase the probability of driving errors and hazardous
driving actions and it is necessary to explicitly understand the endogenous and exogenous …
driving actions and it is necessary to explicitly understand the endogenous and exogenous …
An Advanced Driver Information System at Critical Points in the Multimodal Traffic Network
Enhancing traffic safety is one of the fundamental objectives of Intelligent Transport Systems
(ITS), and it aligns closely with the principles of sustainable transport. Due to specific …
(ITS), and it aligns closely with the principles of sustainable transport. Due to specific …
Self-supervised human mobility learning for next location prediction and trajectory classification
Massive digital mobility data are accumulated nowadays due to the proliferation of location-
based service (LBS), which provides the opportunity of learning knowledge from human …
based service (LBS), which provides the opportunity of learning knowledge from human …
Quinazoline-Schiff base conjugates: in silico study and ADMET predictions as multi-target inhibitors of coronavirus (SARS-CoV-2) proteins
The 2019 coronavirus (COVID-19) pandemic is spreading worldwide, with a dramatic
increase in death without any effective therapeutic treatment available up to now. We …
increase in death without any effective therapeutic treatment available up to now. We …
Efficient fusion decision system for predicting road crash events: a comparative simulator study for imbalance class handling
Z Elamrani Abou Elassad, M Ameksa… - Transportation …, 2024 - journals.sagepub.com
Road crash events are a fact of life. Although significant progress have been made in
adopting machine learning techniques for analyzing road crashes, there has been limited …
adopting machine learning techniques for analyzing road crashes, there has been limited …