Results 41 to 50 of about 288 (174)

LSTM+MA: A Time-Series Model for Predicting Pavement IRI

Infrastructures
The accurate prediction of pavement performance is essential for transportation administration or management to appropriately allocate resources road maintenance and upkeep.
Tianjie Zhang, Alex Smith, Huachun Zhai, Yang Lu   +3 more
doaj   +1 more source

A Machine Learning Approach to Understand the Impact of Temperature and Rainfall Change on Concrete Pavement Performance Based on LTPP Data [PDF]

SVU-International Journal of Engineering Sciences and Applications
Climate change is one of the most concerning global issues and has the potential to influence every aspect of human life. Like different components of society, it can impose significant adverse impacts on pavement infrastructure.
Debo Brata Paul Argha, Md Ashik Ahmed
doaj   +1 more source

Long short‐term memory‐based real‐time prediction models for freezing depth and thawing time in unbound pavement layers

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 20, Page 3182-3196, 18 August 2025.
Abstract The prediction of freezing depth and thawing time of unbound pavement layers in cold regions is a critical task in pavement design and management. This study developed long short‐term memory (LSTM)‐based encoder–decoder models to accurately predict freezing depth and thawing time, with air temperature as the sole input variable.
Y. Ma, S. Park, A. Bae, K. Kwon, H. Choi
wiley   +1 more source

Improved model for pavement performance prediction based on recurrent neural network using LTPP database

International Journal of Transportation Science and Technology
Accurate pavement performance prediction plays a critical role in formulating maintenance and repair strategies for transportation departments, enabling the achievement of better pavement performance with limited financial resources.
Luchuan Chen, Hui Li, Shuo Wang, Fei Shan, Yuzhao Han, Guoqiang Zhong   +5 more
doaj   +1 more source

Performance Evaluation of JPCP with Changes of Pavement Mix Design Using Pavement Management Data

Advances in Civil Engineering, 2019
This study aimed to analyze long-term performance of JPCP (jointed plain concrete pavement) according to changes in standard mix design using evaluation of concrete properties based on Korea HPMS (highway pavement management system) and Korea LTPP (long ...
Han Jin Oh, Jun Young Park, Hyung Bae Kim, Won Kyong Jung, Jung Hun Lee   +4 more
doaj   +1 more source

Machine learning models for predicting the International Roughness Index of asphalt concrete overlays on Portland cement concrete pavements

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 21, Page 3385-3402, 29 August 2025.
ABSTRACT Although estimating the International Roughness Index (IRI) is crucial, previous studies have faced challenges in addressing IRI prediction for asphalt concrete (AC) overlays on Portland cement concrete (PCC) pavements. This study introduces machine learning to predict the IRI of AC overlays on PCC pavements, focusing on incorporating pre ...
K. Kwon, Y. Yeom, Y. J. Shin, A. Bae, H. Choi   +4 more
wiley   +1 more source

A probabilistic approach for modelling deterioration of asphalt surfaces

Journal of the South African Institution of Civil Engineers, 2012
This paper details findings from the New Zealand Transport Agency's research project by Henning and Roux (2008). It forms part of the overall New Zealand Long-term Pavement Performance (LTPP) programme.
T F P Henning, D C Roux
doaj  

Enhancing road safety: developing a neural network-based model for predicting skid resistance in asphalt pavements using LTPP data

Discover Civil Engineering
This study focuses on the critical aspect of skid resistance in asphalt pavements, an essential factor for ensuring road safety. Several factors, including pavement texture, aggregate properties, and environmental conditions, influence skid resistance ...
Tanvir Ahmed, Mayzan Isied, Mena Souliman   +2 more
doaj   +1 more source

Interpretable machine learning framework for resilient modulus estimation using LTPP data for pavements

Case Studies in Construction Materials
The resilient modulus (Mr) is a key indicator of the mechanical performance of pavement subgrade materials. Traditional laboratory testing for Mr is resource intensive and time consuming, making the development of efficient and practical alternatives ...
Ishfaq Rashid Sheikh, Ming Zhang, Xiaohui Sun, Changqing Chen, Xiangsheng Chen, Zijun Dong, Foci Chen   +6 more
doaj   +1 more source

Multiclassification Tampering Detection Algorithm Based on Spatial‐Frequency Fusion and Swin‐T

IET Image Processing, Volume 19, Issue 1, January/December 2025.
This paper presents a novel multi‐class forgery detection approach that combines spatial‐frequency fusion with Swin‐Transformer to enhance robustness against image compression attacks. We develop an innovative framework incorporating frequency domain perception with quantization tables and spatial domain perception with SRM features, along with a ...
Li Li, Kejia Zhang, Jianfeng Lu, ShanQing Zhang, Ning Chu   +4 more
wiley   +1 more source