Analysis of reinforced concrete structures employing Kohonen Self Organizing Map

Omar Al Juboori*, Rabee Rustum

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationProceedings of the 8th International Conference on Structure, Engineering and Environment
EditorsZakaria Hossain
Publication statusPublished - 12 Nov 2022
Event8th International Conference on Structure, Engineering and Environment 2022 - Yokkaichi, Japan
Duration: 10 Nov 202212 Nov 2022
https://www.confsee.com/

Conference

Conference8th International Conference on Structure, Engineering and Environment 2022
Abbreviated titleSEE 2022
Country/TerritoryJapan
CityYokkaichi
Period10/11/2212/11/22
Internet address

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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