AUTHOR=Zhao Bing , Xue Er-Wei , Gu Xin-Bao 

TITLE=Evaluation of coarse aggregate quality grade of recycled concrete based on the principal component analysis-cloud model

JOURNAL=Frontiers in Materials

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/materials/articles/10.3389/fmats.2023.1291434

DOI=10.3389/fmats.2023.1291434

ISSN=2296-8016

ABSTRACT=the quality grade assessment of coarse aggregate in recycled concrete has great significance for engineering quality, so the accurate estimation of its quality grade is vital. However, many factors affect its quality level, and its assessment procedure has a certain fuzziness and randomness. To overcome the above problems, the principal component analysis-cloud model is introduced, it is a combination of the principal component analytical method (PCA) and normal cloud model; it has the advantages of the two method, and it is widely applied to assess the quality level of different construction materials. To evaluate the coarse aggregate quality grade of recycled concrete in the paper, the principal component analytical method (PCA) is applied to reduce the dimension of data and calculate the weight of each index, then a model of coarse aggregate quality based on cloud theory is constructed, and then according to the characteristic parameters of cloud model, the coarse aggregate quality grade is determined. The conclusions are drawn that the method is feasible for the accurate assessment of quality grade