使用比较建模策略，通过傅立叶变换红外光谱预测沥青的低温性能

IF 3.4 3区工程技术 Q2 CONSTRUCTION & BUILDING TECHNOLOGY

Road Materials and Pavement Design Pub Date : 2024-07-31 DOI:10.1080/14680629.2024.2383915

Zonghao Yang, Bo Su, Haibo Ding, Yanjun Qiu, Dongqing Zhong

引用次数: 0

摘要

本文采用偏最小二乘法回归（PLSR）和人工神经网络（ANN）预测了三种沥青低温指标：低温性能等级（LTPG）、低温性能等级（LTPG）和低温性能等级（ANN）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Prediction of asphalt low-temperature performance by FTIR spectra using comparative modelling strategy

In this paper, partial least square regression (PLSR) and artificial neural network (ANN) were used to predict three asphalt low-temperature index: low-temperature performance grade (LTPG), low-tem...

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来源期刊

Road Materials and Pavement Design 工程技术-材料科学：综合

CiteScore

8.10

自引率

8.10%

发文量

105

审稿时长

3 months

期刊介绍： The international journal Road Materials and Pavement Design welcomes contributions on mechanical, thermal, chemical and/or physical properties and characteristics of bitumens, additives, bituminous mixes, asphalt concrete, cement concrete, unbound granular materials, soils, geo-composites, new and innovative materials, as well as mix design, soil stabilization, and environmental aspects of handling and re-use of road materials. The Journal also intends to offer a platform for the publication of research of immediate interest regarding design and modeling of pavement behavior and performance, structural evaluation, stress, strain and thermal characterization and/or calculation, vehicle/road interaction, climatic effects and numerical and analytical modeling. The different layers of the road, including the soil, are considered. Emerging topics, such as new sensing methods, machine learning, smart materials and smart city pavement infrastructure are also encouraged. Contributions in the areas of airfield pavements and rail track infrastructures as well as new emerging modes of surface transportation are also welcome.