2018
DOI: 10.1007/s40091-018-0202-4
|View full text |Cite
|
Sign up to set email alerts
|

Assessing the accuracy of RC design code predictions through the use of artificial neural networks

Abstract: In light of recently published work highlighting the incompatibility between the concepts underlying current code specifications and fundamental concrete properties, the work presented herein focuses on assessing the ability of the methods adopted by some of the most widely used codes of practice for the design of reinforced concrete structures to provide predictions concerning load-carrying capacity in agreement with their experimentally established counterparts. A comparative study is carried out between the… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

1
42
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 30 publications
(43 citation statements)
references
References 13 publications
1
42
0
Order By: Relevance
“…In the present study, MBP ANNs are developed for predicting the load-carrying capacity of RC members at ultimate limit state (ULS), based on the available test data [15]. The flowchart in Fig.…”
Section: Developing Procedures Of Annmentioning
confidence: 99%
See 4 more Smart Citations
“…In the present study, MBP ANNs are developed for predicting the load-carrying capacity of RC members at ultimate limit state (ULS), based on the available test data [15]. The flowchart in Fig.…”
Section: Developing Procedures Of Annmentioning
confidence: 99%
“…5). Data selected from 608 RC beams without stirrups subjected to 3 or 4 point bending tests (describing the effect of various design parameters on the load-carrying capacity and mode of failure of the specimens) has resulted in the formation of a database [15]. Close consideration of the data included in the database reveals some regions that are poorly populated (i.e.…”
Section: Enrichment Of Existing Experimental Databasesmentioning
confidence: 99%
See 3 more Smart Citations