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[HTML][HTML] Review of advanced road materials, structures, equipment, and detection technologies
As a vital and integral component of transportation infrastructure, pavement has a direct and
tangible impact on socio-economic sustainability. In recent years, an influx of …
tangible impact on socio-economic sustainability. In recent years, an influx of …
[HTML][HTML] Machine learning for prediction of the international roughness index on flexible pavements: A review, challenges, and future directions
Timely maintenance of road pavements is crucial to ensure optimal performance. The
accurate prediction of trends in pavement defects enables more efficient allocation of funds …
accurate prediction of trends in pavement defects enables more efficient allocation of funds …
Groundwater quality evaluation using hybrid model of the multi-layer perceptron combined with neural-evolutionary regression techniques: case study of Shiraz plain
H Moayedi, M Salari, AA Dehrashid, BN Le - … Environmental Research and …, 2023 - Springer
In recent decades, qualitative and quantitative assessments of groundwater sources reveal
that efficient and accurate optimization approaches may assist in solving the multiple …
that efficient and accurate optimization approaches may assist in solving the multiple …
Machine learning for predicting concrete carbonation depth: a comparative analysis and a novel feature selection
The accurate prediction of concrete carbonation depth is essential to prevent concrete from
cracking and corrosion. However, identifying the critical parameters affecting carbonation …
cracking and corrosion. However, identifying the critical parameters affecting carbonation …
Compression behavior of the concrete-filled double skin steel tube columns under hydrostatic pressure: Experimental and modeling study
This paper conducted an experimental study focusing on the axial compressive behavior of
circular concrete-encased concrete-filled steel tubular (CFDST) columns composed of a …
circular concrete-encased concrete-filled steel tubular (CFDST) columns composed of a …
Forecasting heating and cooling loads in residential buildings using machine learning: a comparative study of techniques and influential indicators
B Mehdizadeh Khorrami, A Soleimani… - Asian Journal of Civil …, 2024 - Springer
Residential buildings are a significant source of energy consumption and greenhouse gas
emissions, making it crucial to accurately predict their energy demand for reducing their …
emissions, making it crucial to accurately predict their energy demand for reducing their …
[HTML][HTML] A novel technique for multi-objective sustainable decisions for pavement maintenance and rehabilitation
To maintain pavement in good condition while considering financial costs and sustainability,
it is necessary to develop a comprehensive pavement management plan. Pavement …
it is necessary to develop a comprehensive pavement management plan. Pavement …
Evolution of prediction models for road surface irregularity: Trends, methods and future
Y Wu, Y Pang, X Zhu - Construction and Building Materials, 2024 - Elsevier
In the modern era, the importance of prioritizing traffic safety has become increasingly
evident, requiring dedicated focus. An effective strategy for improving traffic safety involves …
evident, requiring dedicated focus. An effective strategy for improving traffic safety involves …
Application of machine learning to child mode choice with a novel technique to optimize hyperparameters
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous
studies have focused on TMC in adults, whereas predicting TMC in children has received …
studies have focused on TMC in adults, whereas predicting TMC in children has received …
Enhancing stock market prediction accuracy with recurrent deep learning models: A case study on the CAC40 index
This paper explores the application of Recurrent Neural Networks (RNNs) and Long Short-
Term Memory (LSTM) networks for stock price prediction over a 10-day horizon. The study …
Term Memory (LSTM) networks for stock price prediction over a 10-day horizon. The study …