Enhancing Engineering and Architectural Design Through Virtual Reality and Machine Learning Integration

Buildings, Год журнала: 2025, Номер 15(3), С. 328 - 328

Опубликована: Янв. 22, 2025

This study introduces a framework that leverages the synergistic potential of Virtual Reality (VR) and Machine Learning (ML) to enhance graphical modeling in engineering architectural design. Traditional clash detection methods Building Information Modeling (BIM) systems are predominantly reactive, identifying discrepancies only after their occurrence, leading costly time-consuming design revisions. By integrating ML algorithms with VR-driven BIM, our approach proactively identifies resolves clashes, as demonstrated across 28 diverse projects. The results indicate reduction clashes by 16% iterative revisions 15%, culminating 12% decrease overall project timelines. research underscores transformative impact combining VR on additive manufacturing (AM) workflows, significantly improving efficiency reducing nature traditional methods. findings highlight framework’s scalability adaptability, promising substantial advancements architecture practices.

Язык: Английский

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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms

Case Studies in Construction Materials, Год журнала: 2024, Номер 21, С. e03935 - e03935

Опубликована: Ноя. 1, 2024

Язык: Английский

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Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 7, 2025

This study identifies a critical knowledge gap, revealing how the deterioration of roads, compounded by extensive usage and additional factors, poses significant risks to road networks' functionality. Without robust fund allocation prioritization strategy, extent this risk may be overlooked, adversely affecting performance essential infrastructure elements. Our research introduces an integrated decision-making model for existing infrastructures address gap. innovative approach combines Geographic Information System (GIS)-based management with enhanced optimization engine via genetic algorithm. The primary aim is precisely determine Maintenance Repair (M&R) interventions tailored condition states, thereby improving Pavement Condition Index (PCI) segments. structured around three key objectives: (1) develop detailed GIS-based database incorporating inspection data attributes proactive M&R decision-making; (2) efficiently allocate funds maintain service delivery on deteriorated roads; (3) pinpoint optimal type timing boost Anticipated results will provide asset managers comprehensive decision support system executing effective practices.

Язык: Английский

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Machine learning techniques for predicting the peak response of reinforced concrete beam subjected to impact loading

Results in Engineering, Год журнала: 2024, Номер unknown, С. 103135 - 103135

Опубликована: Окт. 1, 2024

Язык: Английский

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Multi-objective maintenance strategy for complex systems considering the maintenance uncertain impact by adaptive multi-strategy particle swarm optimization

Reliability Engineering & System Safety, Год журнала: 2024, Номер unknown, С. 110671 - 110671

Опубликована: Ноя. 1, 2024

Язык: Английский

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Integrative strategies for social inclusion and equity: Enhancing refugee access to higher education in Jordan

Heliyon, Год журнала: 2024, Номер 10(11), С. e31762 - e31762

Опубликована: Май 23, 2024

Incorporating sustainability principles into refugee education, an often overlooked yet crucial domain is pivotal for future societal development. Focusing on UNHCR's directive in Jordan, this research delves the nuances of elevating enrollment higher education to 15 % by 2030. The study identifies significant challenges through empirical and theoretical lenses, such as financial impediments, infrastructural deficits, socio-cultural deterrents. A multi-layered solution proposed: instituting targeted scholarship programs, bolstering institutional capacities diverse learners, leveraging digital platforms, fostering global educational partnerships. By strategically enhancing opportunities refugees, nations harness a richer tapestry skilled human capital underscore commitment holistic sustainability, inclusivity, equity.

Язык: Английский

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Assessing impacts of economic and municipality factors on building construction duration using ensemble categorical boosting

Deleted Journal, Год журнала: 2025, Номер 7(6)

Опубликована: Май 25, 2025

Язык: Английский

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Unpacking predictive relationships in graphene oxide-reinforced cementitious nanocomposites: An explainable ensemble learning approach for augmented data

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 144, С. 110123 - 110123

Опубликована: Янв. 25, 2025

Язык: Английский

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Data-driven optimization design method and tool platform for green residential area layout

Journal of Asian Architecture and Building Engineering, Год журнала: 2025, Номер unknown, С. 1 - 17

Опубликована: Янв. 28, 2025

Язык: Английский

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Early warning study of field station process safety based on VMD-CNN-LSTM-self-attention for natural gas load prediction

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 21, 2025

As a high-risk production unit, natural gas supply enterprises are increasingly recognizing the need to enhance safety management. Traditional process warning methods, which rely on fixed alarm values, often fail adequately account for dynamic changes in process. To address this issue, study utilizes deep learning techniques accuracy and reliability of load forecasting. By considering benefits feasibility integrating multiple models, VMD-CNN-LSTM-Self-Attention interval prediction method was innovatively proposed developed. Empirical research conducted using data from field station outgoing loads. The primary model constructed is loads, implements graded mechanism based 85%, 90%, 95% confidence intervals real-time observations. This approach represents novel strategy enhancing enterprise Experimental results demonstrate that outperforms traditional reducing MAE, MAPE, MESE, REMS by 1.13096 m3/h, 1.3504%, 7.6363 1.6743 respectively, while improving R2 0.04698. These findings expected offer valuable insights safe management industry provide new perspectives industry's digital intelligent transformation.

Язык: Английский

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