Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming

Amir Hossein Gandomi; Amir Hossein Alavi; T. O. Ting; Xin She Yang

doi:10.1007/978-3-642-38703-6_66

Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming

Amir Hossein Gandomi, Amir Hossein Alavi, T. O. Ting^*, Xin She Yang

^*Corresponding author for this work

Department of Electrical and Electronic Engineering

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

16 Citations (Scopus)

Abstract

The accurate prediction of the elastic modulus of concrete can be very important in civil engineering applications. We use gene expression programming (GEP) to model and predict the elastic modulus of normal-strength concrete (NSC) and high-strength concrete (HSC). The proposed models can relate the modulus of elasticity of NSC and HSC to their compressive strength, based on reliable experimental databases obtained from the published literature. Our results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC. Furthermore, the comparison study in the present work indicates that the GEP predictions are more accurate than other methods.

Original language	English
Title of host publication	Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings
Pages	564-571
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-38703-6_66
Publication status	Published - 2013
Event	4th International Conference on Advances in Swarm Intelligence, ICSI 2013 - Harbin, China Duration: 12 Jun 2012 → 15 Jun 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7928 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Advances in Swarm Intelligence, ICSI 2013
Country/Territory	China
City	Harbin
Period	12/06/12 → 15/06/12

Keywords

Compressive strength
Formulation
Gene expression programming
Normal and High strength concrete
Tangent elastic modulus

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10.1007/978-3-642-38703-6_66

Cite this

Gandomi, A. H., Alavi, A. H., Ting, T. O., & Yang, X. S. (2013). Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming. In Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings (PART 1 ed., pp. 564-571). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7928 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-38703-6_66

Gandomi, Amir Hossein ; Alavi, Amir Hossein ; Ting, T. O. et al. / Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming. Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings. PART 1. ed. 2013. pp. 564-571 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming",

abstract = "The accurate prediction of the elastic modulus of concrete can be very important in civil engineering applications. We use gene expression programming (GEP) to model and predict the elastic modulus of normal-strength concrete (NSC) and high-strength concrete (HSC). The proposed models can relate the modulus of elasticity of NSC and HSC to their compressive strength, based on reliable experimental databases obtained from the published literature. Our results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC. Furthermore, the comparison study in the present work indicates that the GEP predictions are more accurate than other methods.",

keywords = "Compressive strength, Formulation, Gene expression programming, Normal and High strength concrete, Tangent elastic modulus",

author = "Gandomi, {Amir Hossein} and Alavi, {Amir Hossein} and Ting, {T. O.} and Yang, {Xin She}",

year = "2013",

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booktitle = "Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings",

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Gandomi, AH, Alavi, AH, Ting, TO & Yang, XS 2013, Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming. in Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7928 LNCS, pp. 564-571, 4th International Conference on Advances in Swarm Intelligence, ICSI 2013, Harbin, China, 12/06/12. https://doi.org/10.1007/978-3-642-38703-6_66

Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming. / Gandomi, Amir Hossein; Alavi, Amir Hossein; Ting, T. O. et al.
Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings. PART 1. ed. 2013. p. 564-571 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7928 LNCS, No. PART 1).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming

AU - Gandomi, Amir Hossein

AU - Alavi, Amir Hossein

AU - Ting, T. O.

AU - Yang, Xin She

PY - 2013

Y1 - 2013

N2 - The accurate prediction of the elastic modulus of concrete can be very important in civil engineering applications. We use gene expression programming (GEP) to model and predict the elastic modulus of normal-strength concrete (NSC) and high-strength concrete (HSC). The proposed models can relate the modulus of elasticity of NSC and HSC to their compressive strength, based on reliable experimental databases obtained from the published literature. Our results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC. Furthermore, the comparison study in the present work indicates that the GEP predictions are more accurate than other methods.

AB - The accurate prediction of the elastic modulus of concrete can be very important in civil engineering applications. We use gene expression programming (GEP) to model and predict the elastic modulus of normal-strength concrete (NSC) and high-strength concrete (HSC). The proposed models can relate the modulus of elasticity of NSC and HSC to their compressive strength, based on reliable experimental databases obtained from the published literature. Our results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC. Furthermore, the comparison study in the present work indicates that the GEP predictions are more accurate than other methods.

KW - Compressive strength

KW - Formulation

KW - Gene expression programming

KW - Normal and High strength concrete

KW - Tangent elastic modulus

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Gandomi AH, Alavi AH, Ting TO, Yang XS. Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming. In Advances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings. PART 1 ed. 2013. p. 564-571. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-38703-6_66

Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming

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