Applying Artificial Neural Networks In Construction

Doroshenko, Anna

doi:10.1051/e3sconf/202014301029

Cited by 6 publications

(1 citation statement)

References 78 publications

(75 reference statements)

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“…Recently, versatile strengthening requirements, applied to construction projects in the areas of safety, energy efficiency, cost management, etc., have encouraged the industry to employ new instruments and methods, including more efficient application of digital technologies. Building information modelling (BIM) is one of the fastest developing approaches in use [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Usability engineering of an information model simulating emergency scenarios at construction facilities

2021

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The transition to the construction facilities design, that involves the application of information models, strengthens the requirements for the comfortable perception of such models by their users and consumers. The presented research work has a description of an information model that accompanies a construction facility at each stage of its lifecycle. The article addresses the usability notion in the context of the emergency scenarios’ information modelling at construction facilities. The co-authors offer an infographic model of a building information model lifecycle. The information model lifecycle analysis has given an opportunity to identify the production and consumption stages of an information model. Positions of the stakeholders, involved in the usability engineering of an information model, have been determined.

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Section: Introductionmentioning

confidence: 99%

Usability engineering of an information model simulating emergency scenarios at construction facilities

2021

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Risks assessment in the construction of infrastructure projects using artificial neural networks

Ibrahim

Mohamed

2022

International Journal of Construction Management

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Data Mining preparation: Process, Techniques and Major Issues in Data Analysis

Jassim

Abdulwahid

2021

IOP Conf. Ser.: Mater. Sci. Eng.

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Data preparation is an essential stage in data analysis. Many institutions or companies are interested in converting data into pure forms that can be used for scientific and profit purposes. It helps you set goals regarding system capabilities and features or the benefits your company expects from its investment. This purpose creates an immediate need to review and prepare the data to clean the raw data. In this paper, we highlight the importance of data preparation in data analysis and data extraction techniques, in addition to an integrated overview of relevant recent studies dealing with mining methodology, data types diversity, user interaction, and data mining. Finally, we suggest some potential suggestions for future research and development.

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Applying Artificial Neural Networks In Construction

Cited by 6 publications

References 78 publications

Usability engineering of an information model simulating emergency scenarios at construction facilities

Usability engineering of an information model simulating emergency scenarios at construction facilities

Risks assessment in the construction of infrastructure projects using artificial neural networks

Data Mining preparation: Process, Techniques and Major Issues in Data Analysis

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