Recent advances in applications of artificial intelligence in solid waste management: A review
Efficient management of solid waste is essential to lessen its potential health and
environmental impacts. However, the current solid waste management practices encounter …
environmental impacts. However, the current solid waste management practices encounter …
[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 …
Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction
Growing electric mobility makes it difficult for electric vehicles (EVs) to charge adequately
while charging infrastructure capacities are limited. Due to the prolonged charging times …
while charging infrastructure capacities are limited. Due to the prolonged charging times …
Deep embedded median clustering for routing misbehaviour and attacks detection in ad-hoc networks
A Rajendran, N Balakrishnan, P Ajay - Ad Hoc Networks, 2022 - Elsevier
Due to the properties of ad-hoc networks, it appears that designing sophisticated defence
schemes with more computing capital is impossible in most situations. Recently, an …
schemes with more computing capital is impossible in most situations. Recently, an …
Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Comparative study of machine learning classifiers for modelling road traffic accidents
Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent
years, there has been a growing global interest in analysing RTAs, specifically concerned …
years, there has been a growing global interest in analysing RTAs, specifically concerned …
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 …
[HTML][HTML] Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers
JPSS Madushani, RMK Sandamal… - Transportation …, 2023 - Elsevier
The number of expressway road accidents in Sri Lanka has significantly increased (by 20%)
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
A hybrid approach of random forest and random parameters logit model of injury severity modeling of vulnerable road users involved crashes
Z Sun, D Wang, X Gu, M Abdel-Aty, Y Xing… - Accident Analysis & …, 2023 - Elsevier
Vulnerable road users (VRUs) involved crashes are a major road safety concern due to the
high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity …
high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity …
Ensemble tree-based approach towards flexural strength prediction of frp reinforced concrete beams
Due to rise in infrastructure development and demand for seawater and sea sand concrete,
fiber-reinforced polymer (FRP) rebars are widely used in the construction industry. Flexural …
fiber-reinforced polymer (FRP) rebars are widely used in the construction industry. Flexural …