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Prediction of LWST values using ML and ANN techniques from frcition and texture measuring devices based on long term field data

Mohammad Ahmad Alsheyab Mohammad Ali Khasawneh Danah Hussain Alotaibi Nayeemuddin Mohammed Ahmad Ali Khasawneh

International Journal of Transportation Science and Technology2026，Vol.21Issue(1)：P.228-255,28.

International Journal of Transportation Science and Technology2026，Vol.21Issue(1)：P.228-255,28.DOI:10.1016/j.ijtst.2025.01.015

Prediction of LWST values using ML and ANN techniques from frcition and texture measuring devices based on long term field data

Mohammad Ahmad Alsheyab ¹Mohammad Ali Khasawneh ²Danah Hussain Alotaibi ²Nayeemuddin Mohammed ²Ahmad Ali Khasawneh³

作者信息

1. Department of Civil,Construction and Environmental Engineering,Iowa State University,Ames,IA 50011,United States
2. Department of Civil Engineering,Prince Mohammad Bin Fahd University,Al Khobar 31952,Kingdom of Saudi Arabia
3. Department of Integrated Systems Engineering,The Ohio State University,Columbus,OH 43210,United States
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摘要

关键词

Skid resistance/locked wheel skid trailer(LWST)/Machine learning(ML)/Deep learning/Data imputation

分类

交通工程

引用本文复制引用

Mohammad Ahmad Alsheyab,Mohammad Ali Khasawneh,Danah Hussain Alotaibi,Nayeemuddin Mohammed,Ahmad Ali Khasawneh..Prediction of LWST values using ML and ANN techniques from frcition and texture measuring devices based on long term field data[J].International Journal of Transportation Science and Technology,2026,21(1):P.228-255,28.

International Journal of Transportation Science and Technology

ISSN：2046-0430

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