Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA
%0 Journal Article
%1 arastehkhoshbin2024comparing
%A Arasteh-Khoshbin, Omolbanin
%A Seyedpour, Seyed Morteza
%A Mandl, Luis
%A Lambers, Lena
%A Ricken, Tim
%D 2024
%I Taylor & Francis
%J European journal of environmental and civil engineering
%K oa ubs_10006 ubs_20010 ubs_30097 ubs_40150 unibibliografie wos
%N 2
%P 331-350
%R 10.1080/19648189.2024.2393881
%T Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA
%V 29
@article{arastehkhoshbin2024comparing,
added-at = {2025-03-18T14:53:59.000+0100},
affiliation = {Seyedpour, SM (Corresponding Author), Univ Stuttgart, Inst Struct Mech \& Dynam, Fac Aerosp Engn \& Geodesy, Stuttgart, Germany.
Seyedpour, SM (Corresponding Author), Univ Stuttgart, Inst Struct Mech \& Dynam Aerosp Engn, Fac Aerosp Engn \& Geodesy, Porous Media Lab, Stuttgart, Germany.
Arasteh-Khoshbin, O.; Seyedpour, S. M.; Mandl, L.; Lambers, L.; Ricken, T., Univ Stuttgart, Inst Struct Mech \& Dynam, Fac Aerosp Engn \& Geodesy, Stuttgart, Germany.
Arasteh-Khoshbin, O.; Seyedpour, S. M.; Lambers, L.; Ricken, T., Univ Stuttgart, Inst Struct Mech \& Dynam Aerosp Engn, Fac Aerosp Engn \& Geodesy, Porous Media Lab, Stuttgart, Germany.},
author = {Arasteh-Khoshbin, Omolbanin and Seyedpour, Seyed Morteza and Mandl, Luis and Lambers, Lena and Ricken, Tim},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e4470e95ba172771b3c5f480b78e153a/unibiblio},
doi = {10.1080/19648189.2024.2393881},
interhash = {d29fca572c3bd0719c2f956c5c086e66},
intrahash = {e4470e95ba172771b3c5f480b78e153a},
issn = {{1964-8189} and {2116-7214}},
journal = {European journal of environmental and civil engineering},
keywords = {oa ubs_10006 ubs_20010 ubs_30097 ubs_40150 unibibliografie wos},
language = {eng},
number = 2,
pages = {331-350},
publisher = {Taylor & Francis},
research-areas = {Engineering},
timestamp = {2025-03-18T14:53:59.000+0100},
title = {Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA},
unique-id = {WOS:001325309900001},
volume = 29,
year = 2024
}
