Analysis of reinforced concrete structures employing Kohonen Self Organizing Map

Omar Al Juboori; Rabee Rustum

Analysis of reinforced concrete structures employing Kohonen Self Organizing Map

Omar Al Juboori^*, Rabee Rustum

^*Corresponding author for this work

School of Energy, Geoscience, Infrastructure and Society

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Reinforced Cement Concrete (RCC) structure is most widely used in the construction industry alongside other types of structures such as steel structures, wooden structures and many other systems used globally. This paper will employ Artificial Intelligent (AI) techniques for modelling the (RCC) elements in the buildings using the Kohonen Self Organizing Map (KSOM) and a comparison between this technique and other techniques used in the field, such as the Artificial Neural Network (ANN). The results show that the Kohonen Self Organizing Map (KSOM) is an attractive tool for modelling reinforced concrete structures. Moreover, this technique offers a magnificent tool for high dimensional data visualization.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Structure, Engineering and Environment
Editors	Zakaria Hossain
Publication status	Published - 12 Nov 2022
Event	8th International Conference on Structure, Engineering and Environment 2022 - Yokkaichi, Japan Duration: 10 Nov 2022 → 12 Nov 2022 https://www.confsee.com/

Conference

Conference	8th International Conference on Structure, Engineering and Environment 2022
Abbreviated title	SEE 2022
Country/Territory	Japan
City	Yokkaichi
Period	10/11/22 → 12/11/22
Internet address	https://www.confsee.com/

Keywords

Reinforced Cement Concrete
Artificial Intelligent
Kohonen Self Organizing Map
Artificial Neural Network

ASJC Scopus subject areas

Civil and Structural Engineering

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title = "Analysis of reinforced concrete structures employing Kohonen Self Organizing Map",

abstract = "Reinforced Cement Concrete (RCC) structure is most widely used in the construction industry alongside other types of structures such as steel structures, wooden structures and many other systems used globally. This paper will employ Artificial Intelligent (AI) techniques for modelling the (RCC) elements in the buildings using the Kohonen Self Organizing Map (KSOM) and a comparison between this technique and other techniques used in the field, such as the Artificial Neural Network (ANN). The results show that the Kohonen Self Organizing Map (KSOM) is an attractive tool for modelling reinforced concrete structures. Moreover, this technique offers a magnificent tool for high dimensional data visualization.",

keywords = "Reinforced Cement Concrete, Artificial Intelligent, Kohonen Self Organizing Map, Artificial Neural Network",

author = "{Al Juboori}, Omar and Rabee Rustum",

year = "2022",

month = nov,

day = "12",

language = "English",

isbn = "9784909106094",

editor = "Zakaria Hossain",

booktitle = "Proceedings of the 8th International Conference on Structure, Engineering and Environment",

note = "8th International Conference on Structure, Engineering and Environment 2022, SEE 2022 ; Conference date: 10-11-2022 Through 12-11-2022",

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T1 - Analysis of reinforced concrete structures employing Kohonen Self Organizing Map

AU - Al Juboori, Omar

AU - Rustum, Rabee

PY - 2022/11/12

Y1 - 2022/11/12

N2 - Reinforced Cement Concrete (RCC) structure is most widely used in the construction industry alongside other types of structures such as steel structures, wooden structures and many other systems used globally. This paper will employ Artificial Intelligent (AI) techniques for modelling the (RCC) elements in the buildings using the Kohonen Self Organizing Map (KSOM) and a comparison between this technique and other techniques used in the field, such as the Artificial Neural Network (ANN). The results show that the Kohonen Self Organizing Map (KSOM) is an attractive tool for modelling reinforced concrete structures. Moreover, this technique offers a magnificent tool for high dimensional data visualization.

AB - Reinforced Cement Concrete (RCC) structure is most widely used in the construction industry alongside other types of structures such as steel structures, wooden structures and many other systems used globally. This paper will employ Artificial Intelligent (AI) techniques for modelling the (RCC) elements in the buildings using the Kohonen Self Organizing Map (KSOM) and a comparison between this technique and other techniques used in the field, such as the Artificial Neural Network (ANN). The results show that the Kohonen Self Organizing Map (KSOM) is an attractive tool for modelling reinforced concrete structures. Moreover, this technique offers a magnificent tool for high dimensional data visualization.

KW - Reinforced Cement Concrete

KW - Artificial Intelligent

KW - Kohonen Self Organizing Map

KW - Artificial Neural Network

UR - https://uploads.documents.cimpress.io/v1/uploads/a1399cb1-4e33-4573-874d-6599a12441d4~110/original?tenant=vbu-digital

M3 - Conference contribution

SN - 9784909106094

BT - Proceedings of the 8th International Conference on Structure, Engineering and Environment

A2 - Hossain, Zakaria

T2 - 8th International Conference on Structure, Engineering and Environment 2022

Y2 - 10 November 2022 through 12 November 2022

ER -

Analysis of reinforced concrete structures employing Kohonen Self Organizing Map

Abstract

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Keywords

ASJC Scopus subject areas

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