Prediction of asphalt complex viscosity by artificial neural network based on Fourier transform infrared spectroscopy-Reference-Cited by-同舟云学术

Prediction of asphalt complex viscosity by artificial neural network based on Fourier transform infrared spectroscopy

Published:2019-04-22 Issue:14 Volume:37 Page:1731-1737
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Han Sen¹,Zhang Zhuang¹,Yuan Ye²,Wang Kang³

Affiliation:

1. College of Highway, Chang'an University, Xi’an, China;

2. Chengdu Architectural Design & Research Institute, Chengdu, China;

3. College of Science, Chang'an University, Xi'an, China

Funder

Research project of Transportation Department of Gansu Province of China

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2019.1605377

Reference11 articles.

1. An artificial neural network model for predicting the CO2 reactivity of carbon anodes used in the primary aluminum production

2. Investigation of Reclaimed Asphalt Pavement blending efficiency through GPC and FTIR

3. Investigation of complex modulus of base and SBS modified bitumen with artificial neural networks

4. Modeling the effects of temperature, pressure, and composition on the viscosity of crude oil mixtures

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unveiling micro-macro links in asphalt: An in-depth analysis of characterization and simulation approaches;Fuel;2025-01

2. Contributions of fourier-transform infrared spectroscopy technologies to the research of asphalt materials: A comprehensive review;Fuel;2024-09

3. Prediction of asphalt low-temperature performance by FTIR spectra using comparative modelling strategy;Road Materials and Pavement Design;2024-07-31

4. Application of machine learning models for prediction of rheological properties of wax-modified asphalt binders;Construction and Building Materials;2023-09

5. Study on aging mechanism of SBS/SBR compound-modified asphalt based on molecular dynamics;REVIEWS ON ADVANCED MATERIALS SCIENCE;2023-01-01