BIM performance assessment system using a K-means clustering algorithm

Kim, Hyeon-Seung; Kim, Sung-Keun; Kang, Leen-Seok

doi:10.1080/13467581.2020.1800471

Cited by 18 publications

(27 citation statements)

References 13 publications

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“…However, the most challenging part of this type of qualitative assessment is outlining the qualitative BIM performance assessment tools for the operational strategy. Kim et al [112] have solved this matter by proposing a method based on the k-means clustering algorithm. The solution implies that the BIM performance assessment system enables both the evaluation of the current BIM execution ability and the corresponding prediction of the cost-effectiveness before and after implementation of BIM projects through a comparison with other projects.…”

Section: K-means Algorithmmentioning

confidence: 99%

“…Searching for similar project groups can be facilitated using the k-means algorithm, since this algorithm is very efficient in clustering analysis, which quickly results in stable results [112]. A procedure runs the processes associated with the k-means algorithm.…”

Section: K-means Algorithmmentioning

confidence: 99%

“…The data used for these clusters can be determined by the similarity ratio between the case and target projects, as depicted in Table 3. The metrics are used in evaluating project information and assessing BIM tool, BIM application phase, performance capability, costs, and usage frequency [112]. Table 3.…”

Section: K-means Algorithmmentioning

confidence: 99%

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The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review

et al. 2022

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This review targets the BIM interface, the BIM multi-model approach, and the role of employing algorithms in BIM optimization to introduce the need for automation in the BIM technique, instead of complicating manual procedures in order to reduce possible errors. The challenge with adopting BIM lies in the limiting ability of computer-aided design (CAD) to generate a read-able and straightforward Revit by BIM, requiring the homogeneous data format to be generalized better and maintain a super data mod. Furthermore, the communication and management inter-face (CMI) faces some shortcomings due to limitations in its ability to recognize the role of the interface during the project construction phase. This review demonstrates several proposals to simplify the interface, in order to facilitate better communication amongst participants. The industry foundation class (IFC) model requires a new technique to unlock the potential future of intelligent buildings using the BIM multi-model approach integrated with the Internet of Things (IoT). Trials conducted to enhance the BIM model lack advanced methods for optimizing cost, energy consumption, labor, material movement, and the size of layout of the project, by utilizing heuristic, metaheuristic, and k-mean algorithms. The enhancement of BIM could involve algorithms to achieve better productivity, safety, cost, time, and construction frameworks. The review shows that some gaps and limitations still exist, especially considering the potential link between BIM and building management system (BMS) and the level of influence of the BIM-IoT prototype. Future work should find the best approach to solve facility management within the dynamic model, which is still under investigation.

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Section: K-means Algorithmmentioning

confidence: 99%

Section: K-means Algorithmmentioning

confidence: 99%

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The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review

et al. 2022

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“…Singh et al (2019) penelitian di bidang kesehatan di mana sistem yang dibuat dengan metode ini dapat membantu dalam mengusulkan pendekatan hibrida cerdas untuk diagnosis penyakit hepatitis [6]. Kim et al (2021) penelitian di bidang bisnis di mana sistem yang dibuat dengan metode ini dapat memprediksi dan mengevaluasi efektivitas biaya pengenalan dan pengoperasian BIM [7]. Febriyati et al (2020) penelitian di bidang perekonomian di mana sistem yang dibuat dapat membantu dan mempermudah dalam mengelompokkan laju pertumbuhan menurut bidang usaha di Kota Surabaya, sehingga dapat diketahui sektor mana saja yang mengalami pertumbuhan tinggi atau rendah [8].…”

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Algoritma K-Means Clustering dalam Mengklasifikasi Data Daerah Rawan Tindak Kriminalitas (Polres Kepulauan Mentawai)

2021

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Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and threaten their inner and outer peace. The research location is the Mentawai Islands Police, which is an agency that can provide security and protection for the community, especially those in the Mentawai Islands Regency. The problem is that it is difficult for the Mentawai Islands Police to classify areas that are prone to crime in the most vulnerable, moderately vulnerable and not vulnerable categories. Especially considering the condition of the Mentawai, there are four large islands consisting of 10 sub-districts, where crime is increasing every year, especially those in the Mentawai Islands Regency area such as motor vehicle theft. Based on the background of the problem above, the researcher is interested in taking research in creating a system to predict the crime rate in the Mentawai Islands Regency in order to anticipate the surge in crime that will come. The method used is the K-Means Clustering Algorithm as a non-hierarchical data clustering method to partition existing data into one or more clusters or groups. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. Clustering is one of the data mining techniques used to get groups of objects that have common characteristics in large enough data. The data used is data on cases of criminal theft of motor vehicles for the last 5 years from 2016 to 2020. The results of the test show that South Sipora District is an area prone to the crime of motor vehicle theft.

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“…По мере того, как внедрение информационного моделирования зданий (BIM) становится повсеместным, а уровень его применения повышается, потребность во включении предметно-ориентированных знаний в инструменты разработки BIM также возрастает [7 -9]. Существуют исследования о факторах оценки инвестиционной стоимости BIM [10].…”

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Application of Bim-Technologies in the Development of Archetectural, Structural and Organizational-Technological Sulutiins of an Industrial Building

Шутова¹,

Plahutina

Kuzheleva

2021

Construction and Architecture

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Recently, more and more attention has been paid to the potential benefits of BIM in construction. Effective communication between stakeholders at all stages of the building life cycle has become a major challenge in the global industry. The implementation of Building Information Modeling (BIM) has been recognized as a productive approach to solving this problem. A literature review identified key issues related to the use and implementation of BIM. This article presents the design of an industrial building (architectural, structural, organizational and technical solutions) using four software systems, shows the practical experience of optimizing the construction of a workshop based on the data of the information model of the building.

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BIM performance assessment system using a K-means clustering algorithm

Cited by 18 publications

References 13 publications

The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review

The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review

Algoritma K-Means Clustering dalam Mengklasifikasi Data Daerah Rawan Tindak Kriminalitas (Polres Kepulauan Mentawai)

Application of Bim-Technologies in the Development of Archetectural, Structural and Organizational-Technological Sulutiins of an Industrial Building

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