Recurrent Neural Networks Considering Natural Conditions for Determination of the Reinforcement Degrees when Constructing Infrastructure Structures

In recent years, the use of AI has been promoted in the construction industry to solve labour shortages. This study focuses on determining the reinforcement degree when constructing a kind of infrastructure, which has required the empirical knowledge of experts, and proposes a machine learning method to automate the process. The target structure is divided into many sections, and the reinforcement degree for each section needs to be determined based on observation data.

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Publication Details

Journal
Transactions of the Institute of Systems Control and Information Engineers
Published
2024-09-15
DOI
https://doi.org/10.5687/iscie.37.237
Primary Topic
Geodetic Measurements and Engineering Structures
Type
article
Field-Weighted Citation Impact
0.00
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article

Recurrent Neural Networks Considering Natural Conditions for Determination of the Reinforcement Degrees when Constructing Infrastructure Structures

Yeboon Yun, Keiji Tatsumi, Haruhisa Miyahara
Transactions of the Institute of Systems Control and Information Engineers
Geodetic Measurements and Engineering Structures
article

Recurrent Neural Networks Considering Natural Conditions for Determination of the Reinforcement Degrees when Constructing Infrastructure Structures

Yeboon Yun, Keiji Tatsumi, Haruhisa Miyahara
article en

Abstract

In recent years, the use of AI has been promoted in the construction industry to solve labour shortages. This study focuses on determining the reinforcement degree when constructing a kind of infrastructure, which has required the empirical knowledge of experts, and proposes a machine learning method to automate the process. The target structure is divided into many sections, and the reinforcement degree for each section needs to be determined based on observation data.

Transactions of the Institute of Systems Control and Information EngineersVol. 37(9)
Kansai University (JP), The University of Osaka (JP)
Industry, innovation and infrastructure
Openalex Percentile: Top 74%
Geodetic Measurements and Engineering Structures
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