Road traffic accidents: An overview of data sources, analysis techniques and contributing factors
Road traffic accidents are one among the world's leading causes of injuries and fatalities
and hence represent an important field of research towards the use of traffic accident …
and hence represent an important field of research towards the use of traffic accident …
[HTML][HTML] A review on neural network techniques for the prediction of road traffic accident severity
The occurrence rate of death and injury due to road traffic accidents is rising increasingly
globally day by day. For several decades, the focus of research has been on getting a …
globally day by day. For several decades, the focus of research has been on getting a …
LSTM networks to improve the prediction of harmful algal blooms in the west coast of Sabah
FN Yussof, N Maan, MN Md Reba - International Journal of …, 2021 - mdpi.com
Harmful algal bloom (HAB) events have alarmed authorities of human health that have
caused severe illness and fatalities, death of marine organisms, and massive fish killings …
caused severe illness and fatalities, death of marine organisms, and massive fish killings …
A data-driven, kinematic feature-based, near real-time algorithm for injury severity prediction of vehicle occupants
Accurate real-time prediction of occupant injury severity in unavoidable collision scenarios is
a prerequisite for enhancing road traffic safety with the development of highly automated …
a prerequisite for enhancing road traffic safety with the development of highly automated …
Fusion convolutional neural network-based interpretation of unobserved heterogeneous factors in driver injury severity outcomes in single-vehicle crashes
In this study, a fusion convolutional neural network with random term (FCNN-R) model is
proposed for driver injury severity analysis. The proposed model consists of a set of sub …
proposed for driver injury severity analysis. The proposed model consists of a set of sub …
Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system
This study proposes a neural network (NN) model to predict and simulate the propagation of
vehicular traffic noise in a dense residential area at the New Klang Valley Expressway …
vehicular traffic noise in a dense residential area at the New Klang Valley Expressway …
Application of deep learning techniques in predicting motorcycle crash severity
Abstract Machine learning (ML) techniques play a crucial role in today's modern world. Over
the last years, road traffic safety is one of the applications where ML‐methods have been …
the last years, road traffic safety is one of the applications where ML‐methods have been …
[HTML][HTML] Influence of the human development index, motorcycle growth and policy intervention on road traffic fatalities–A case study of Vietnam
Motorcycle ownership in Vietnam has increased exponentially during the last two decades.
As a result, traffic congestion, emissions, and traffic safety have been on the rise. Of …
As a result, traffic congestion, emissions, and traffic safety have been on the rise. Of …
Forecasting road traffic accident using deep artificial neural network approach in case of Oromia Special Zone
Millions of people are dying, and billions of properties are damaged by road traffic accidents
each year worldwide. In the case of our country Ethiopia, the effect of traffic accidents is even …
each year worldwide. In the case of our country Ethiopia, the effect of traffic accidents is even …
Aris: A real time edge computed accident risk inference system
To deploy an intelligent transport system in urban environment, an effective and real-time
accident risk prediction method is required that can help maintain road safety, provide …
accident risk prediction method is required that can help maintain road safety, provide …