Machine learning in civil engineering - important issues and challenges. Julien, B. In of Computing in Civil Engineering (New York), pages 877–884, 1994. Number: 1 tex.document_type: Conference Paper tex.source: Scopus![Machine learning in civil engineering - important issues and challenges [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex In recent years, machine learning techniques have been applied to help overcome the knowledge acquisition bottleneck of knowledge-based systems in civil engineering. This paper identifies a number of important requirements of civil engineering machine learning problems. Preliminary results on several test cases serve to illustrate some of these key issues. The paper concludes on the central challenges for the successful automated acquisition of relevant civil engineering knowledge.
@inproceedings{Julien1994877,
series = {Computing in {Civil} {Engineering} ({New} {York})},
title = {Machine learning in civil engineering - important issues and challenges},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0028602075&partnerID=40&md5=f767e086c198ea46347375debb4f3e7f},
abstract = {In recent years, machine learning techniques have been applied to help overcome the knowledge acquisition bottleneck of knowledge-based systems in civil engineering. This paper identifies a number of important requirements of civil engineering machine learning problems. Preliminary results on several test cases serve to illustrate some of these key issues. The paper concludes on the central challenges for the successful automated acquisition of relevant civil engineering knowledge.},
author = {Julien, Benoit},
year = {1994},
note = {Number: 1
tex.document\_type: Conference Paper
tex.source: Scopus},
keywords = {\#nosource},
pages = {877--884},
}
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