Recent advances in applications of artificial intelligence in solid waste management: A review

I Ihsanullah, G Alam, A Jamal, F Shaik - Chemosphere, 2022 - Elsevier
Efficient management of solid waste is essential to lessen its potential health and
environmental impacts. However, the current solid waste management practices encounter …

[HTML][HTML] A new pedestrian crossing level of service (PCLOS) method for promoting safe pedestrian crossing in urban areas

T Ahmed, M Moeinaddini, M Almoshaogeh… - International journal of …, 2021 - mdpi.com
Crosswalks are critical locations in the urban transport network that need to be designed
carefully as pedestrians are directly exposed to vehicular traffic. Although various methods …

Predicting the travel mode choice with interpretable machine learning techniques: A comparative study

MT Kashifi, A Jamal, MS Kashefi… - Travel Behaviour and …, 2022 - Elsevier
Prediction of mode choice for travelers has been the subject of keen interest among
transportation planners. Traditionally, mode choice analysis is conducted by statistical …

Prediction of electric vehicle charging duration time using ensemble machine learning algorithm and Shapley additive explanations

I Ullah, K Liu, T Yamamoto, M Zahid… - International Journal of …, 2022 - Wiley Online Library
Electric vehicles (EVs) are the most important components of smart transportation systems.
Limited driving range, prolonged charging times, and inadequate charging infrastructure are …

Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time

I Ullah, K Liu, T Yamamoto, M Shafiullah… - Transportation …, 2023 - Taylor & Francis
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …

Transparent deep machine learning framework for predicting traffic crash severity

K Sattar, F Chikh Oughali, K Assi, N Ratrout… - Neural Computing and …, 2023 - Springer
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 …

[HTML][HTML] Machine learning for road traffic accident improvement and environmental resource management in the transportation sector

M Megnidio-Tchoukouegno, JA Adedeji - Sustainability, 2023 - mdpi.com
Despite the measures put in place in different countries, road traffic fatalities are still
considered one of the leading causes of death worldwide. Thus, the reduction of traffic …

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 …

[HTML][HTML] Injury severity analysis of highway-rail grade crossing crashes in non-divided two-way traffic scenarios: A random parameters logit model

Q Ren, M Xu - Multimodal Transportation, 2024 - Elsevier
Highway-rail grade crossing (HRGC) crashes in non-divided two-way traffic scenarios have
caused numerous fatalities and injuries over the years. Although crucial to the safety of …

[HTML][HTML] Ensemble tree-based approach towards flexural strength prediction of frp reinforced concrete beams

MN Amin, M Iqbal, K Khan, MG Qadir, FI Shalabi… - Polymers, 2022 - mdpi.com
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 …