Assessing artificial neural network performance for predicting interlayer conditions and layer modulus of multi-layered flexible pavement-Reference-Cited by-同舟云学术

Assessing artificial neural network performance for predicting interlayer conditions and layer modulus of multi-layered flexible pavement

Published:2020-04 Issue:2 Volume:14 Page:487-500
ISSN:2095-2430
Container-title:Frontiers of Structural and Civil Engineering
language:en
Short-container-title:Front. Struct. Civ. Eng.

Author:

You Lingyun,Yan Kezhen,Liu Nengyuan

Publisher

Springer Science and Business Media LLC

Subject

Architecture,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11709-020-0609-4.pdf

Reference78 articles.

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3. Lv S, Fan X, Xia C, Zheng J, Chen D, You L. Characteristics of moduli decay for the asphalt mixture under different loading conditions. Applied Sciences (Basel, Switzerland), 2018, 8(5): 840

4. Mehta Y, Roque R. Evaluation of FWD data for determination of layer moduli of pavements. Journal of Materials in Civil Engineering, 2003, 15(1): 25–31

5. Nazzal M, Abu-Farsakh M, Alshibli K, Mohammad L. Evaluating the light falling weight deflectometer device for in situ measurement of elastic modulus of pavement layers. Transportation Research Record: Journal of the Transportation Research Board, 2016, 1: 13–22

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