A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms to predict carbonation depth of recycled aggregate concrete

{{article.zuoZheEn}}

PDF(21511 KB)
PDF(21511 KB)
Front. Struct. Civ. Eng. ›› 2024, Vol. 18 ›› Issue (1) : 30-50. DOI: 10.1007/s11709-024-1041-y
RESEARCH ARTICLE

A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms to predict carbonation depth of recycled aggregate concrete

  • {{article.zuoZheEn}}
Author information +
History +

Highlights

{{article.highlightEn}}

Abstract

{{article.abstractEn}}

Author summary

{{article.authorSummayEn}}

Graphical abstract

Keywords

Cite this article

EndNote

Ris (Procite)

Bibtex

Download citation ▾
{{article.zuoZheEn_L}}. {{article.titleEn}}. Front. Struct. Civ. Eng., 2024, 18(1): 30‒50 https://doi.org/10.1007/s11709-024-1041-y

References

Publishing order | Descend order by publishing year | Descend order by cited within

References

{{article.reference}}

RIGHTS & PERMISSIONS

{{article.copyright.year}} {{article.copyright.holder}}
PDF(21511 KB)

Accesses

Citations

Detail
Sections
Recommended

/

〈 〉