[HTML][HTML] Comparing the efficiency of different computation intelligence techniques in predicting accident frequency
Until now, considerable efforts have been made to determine which modelling technique
performs the best for predicting accident frequency based on crash data. In this regard, the …
performs the best for predicting accident frequency based on crash data. In this regard, the …
Comparison analysis of tree based and ensembled regression algorithms for traffic accident severity prediction
Rapid increase of traffic volume on urban roads over time has changed the traffic scenario
globally. It has also increased the ratio of road accidents that can be severe and fatal in the …
globally. It has also increased the ratio of road accidents that can be severe and fatal in the …
Transparent deep machine learning framework for predicting traffic crash severity
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …
studies. A better understanding of crash severity risk factors is vital for the proactive …
An international review of challenges and opportunities in development and use of crash prediction models
Purpose Over the past 10 years, building on road infrastructure data, crash prediction
models (CPMs) have become fundamental scientific tools for road safety management …
models (CPMs) have become fundamental scientific tools for road safety management …
Classification of motor vehicle crash injury severity: A hybrid approach for imbalanced data
This study aims to classify the injury severity in motor-vehicle crashes with both high
accuracy and sensitivity rates. The dataset used in this study contains 297,113 vehicle …
accuracy and sensitivity rates. The dataset used in this study contains 297,113 vehicle …
Prediction and analysis of the severity and number of suburban accidents using logit model, factor analysis and machine learning: a case study in a developing …
The purpose of this study is to investigate and determine the factors affecting vehicle and
pedestrian accidents taking place in the busiest suburban highway of Guilan Province …
pedestrian accidents taking place in the busiest suburban highway of Guilan Province …
Potential application of artificial neural network (ANN) analysis method on Malaysian road crash data
AS Jamaludin, ANSZ Abidin… - Journal of Modern …, 2021 - journal.ump.edu.my
By allowing the movement of commodities and people, road transportation benefits both
nations and people. This provides improved access to work opportunities, educational …
nations and people. This provides improved access to work opportunities, educational …
A new methodology for accidents analysis: the case of the State Road 36 in Italy
F Borghetti, G Marchionni, M De Bianchi… - … journal of transport …, 2021 - re.public.polimi.it
Every year more than 1.35 million people die for road accidents and several million suffer
serious injuries, which force them to live with compromised health conditions. Over the last …
serious injuries, which force them to live with compromised health conditions. Over the last …
Causal analysis and classification of traffic crash injury severity using machine learning algorithms
Objectives Causal analysis and classification of injury severity applying non-parametric
methods for traffic crashes have received limited attention. This study presents a …
methods for traffic crashes have received limited attention. This study presents a …
Development of model for road crashes and identification of accident spots
R Bhavsar, A Amin, L Zala - International journal of intelligent …, 2021 - Springer
The aim of this study is to assess the safety of multi-lane rural highway in India. This paper
shows the application of a generalized linear modeling technique for the analysis of road …
shows the application of a generalized linear modeling technique for the analysis of road …