RETRACTED ARTICLE: Research on Construction Engineering Quality Management Based on Building Information Model and Computer Big Data Mining

Sun, He; Wang, Lichen; Yang, Zhenliang; Xie, Jun

doi:10.1007/s13369-021-05601-y

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…Padded matrix PA for each color, the padding factor must equal the window used for filtering, here we use PF equal [24,25] to allow us to create a window of size 15 by 15.…”

Section: The Proposed Filtermentioning

confidence: 99%

Enhanced Average Filtering Technique for Mitigating Salt and Pepper Noise in High-Resolution Color Images

Khrisat¹

2023

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Digital color images play a crucial role in various critical applications, necessitating the development of effective noise reduction techniques to preserve image quality and characteristics. Salt and pepper noise, in particular, can significantly degrade digital image quality, with the extent of the impact contingent upon image size and noise ratio. Existing methods reliant on arithmetic mean and median filtering have proven inadequate for addressing high noise ratios. In this study, we propose and implement a novel average filter-an enhancement over traditional mean filters-to efficiently mitigate salt and pepper noise, specifically in cases with high noise ratios. Our results demonstrate the superior performance of the proposed filter in terms of preserving image quality and reducing noise, as evidenced by improved maximum auto-correlation factors and peak signal-to-noise ratios.

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“…Padded matrix PA for each color, the padding factor must equal the window used for filtering, here we use PF equal [24,25] to allow us to create a window of size 15 by 15.…”

Section: The Proposed Filtermentioning

confidence: 99%

Enhanced Average Filtering Technique for Mitigating Salt and Pepper Noise in High-Resolution Color Images

Khrisat¹

2023

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“…Several models are assessed, and the ones with the best tolerance and high accuracy are selected and used for obtaining predictive results. In construction, data mining has been reported in waste management [97], BIM-based construction engineering quality management [98], and other relevant areas. Data mining detects useful regularities and information necessary for decision making for construction management projects.…”

Section: Data Miningmentioning

confidence: 99%

Big Data in Construction: Current Applications and Future Opportunities

Munawar

Ullah

Qayyum

et al. 2022

BDCC

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Big data have become an integral part of various research fields due to the rapid advancements in the digital technologies available for dealing with data. The construction industry is no exception and has seen a spike in the data being generated due to the introduction of various digital disruptive technologies. However, despite the availability of data and the introduction of such technologies, the construction industry is lagging in harnessing big data. This paper critically explores literature published since 2010 to identify the data trends and how the construction industry can benefit from big data. The presence of tools such as computer-aided drawing (CAD) and building information modelling (BIM) provide a great opportunity for researchers in the construction industry to further improve how infrastructure can be developed, monitored, or improved in the future. The gaps in the existing research data have been explored and a detailed analysis was carried out to identify the different ways in which big data analysis and storage work in relevance to the construction industry. Big data engineering (BDE) and statistics are among the most crucial steps for integrating big data technology in construction. The results of this study suggest that while the existing research studies have set the stage for improving big data research, the integration of the associated digital technologies into the construction industry is not very clear. Among the future opportunities, big data research into construction safety, site management, heritage conservation, and project waste minimization and quality improvements are key areas.

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“…The score of the evaluation index system is shown in Table 2, and the subjective weight of the final index is shown in Table 3. The initial matrix is established according to the PWL score value of each evaluation index, and the objective weights shown in Table 4 were obtained by using the entropy weight method calculation Formulas (10) and (11). Finally, the subjective and objective combination weights were obtained according to Formula (12).…”

Section: Application Case Studymentioning

confidence: 99%

“…At present, many industrial sectors in China are accelerating the development of information technology as part of the process of digital transformation and this involves both digitization of data from manual recording to digital systems as well as digitalization of existing business processes into digital systems. For example, Sun [10] and others have applied the building information modeling (BIM) system to the quality management of construction engineering for the purpose of quality evaluation. Furthermore, Zhong [11] and others have applied Internet of Things (IoT) technology to the analysis of bridge construction management for information collection.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

Zhang

Philbin

et al. 2021

Buildings

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With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

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RETRACTED ARTICLE: Research on Construction Engineering Quality Management Based on Building Information Model and Computer Big Data Mining

Cited by 8 publications

References 26 publications

Enhanced Average Filtering Technique for Mitigating Salt and Pepper Noise in High-Resolution Color Images

Enhanced Average Filtering Technique for Mitigating Salt and Pepper Noise in High-Resolution Color Images

Big Data in Construction: Current Applications and Future Opportunities

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

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