Prediction of bending strength of glass fiber reinforced methacrylate-based pipeline UV-CIPP rehabilitation materials based on machine learning

Author:

Xia Yangyang,Zhang ChaoORCID,Wang Cuixia,Liu Hongjin,Sang Xinxin,Liu Ren,Zhao Peng,An Guanfeng,Fang Hongyuan,Shi Mingsheng,Li Bin,Yuan Yiming,Liu BokaiORCID

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference35 articles.

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3. Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models;Asteris;Cem. Concr. Res.,2021

4. ASTM, I., 2017. Standard Test Methods for Flexural Properties of Unreinforced and Reinforced Plastics and Electrical Insulating Materials, ASTM-790-2017.

5. Analysis of a cured-in-place pressure pipe liner spanning circular voids;Brown;Tunn. Undergr. Space Technol.,2020

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