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Pedestrian wind flow prediction using spatial-frequency generative adversarial network

Building Simulation 2024年第2期17卷 319-334页

作者： Pengyue Wang Maozu Guo Yingeng Cao Shimeng Hao Xiaoping Zhou Lingling Zhao School of Architecture and Urban Planning Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical *** learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind ***,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow *** study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow *** the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial *** information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency *** spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced *** results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,*** also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind *** reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding *** enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind *** proposed spatial-frequen

关键词： pedestrian wind flow prediction generative adversarial network Gaussian kernel wavelet transform objective function

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The Resilience of Smart Cities: A System Analysis of Seven Megacities in China

The Resilience of Smart Cities: A System Analysis of Seven M...

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2024 International Conference on Construction and Real Estate Management: ESG Development in the Construction Industry, ICCREM 2024

作者： Wu, Zijun He, Xi Huang, Daohan School of Urban Economics and Management Beijing Univ. of Civil Engineering and Architecture Beijing China

ISBN: (数字)9780784485910

ISBN: (纸本)9780784485910

The construction of smart cities is regarded as an effective means to address the urban diseases. However, whether the construction of smart cities can enhance urban resilience remains to be further explored. This paper builds a smart city resilience evaluation index system, including economic, governance, living, transportation, civil, and environmental resilience. Seven megacities in China are employed to conduct empirical analysis with the built index. The results indicate that the resilience level of the seven megacities is moderately high and showing an upward trend, with beijing, Shanghai, and Guangzhou exhibiting high resilience and good development, progressing from moderately resilient cities to strongly resilient ones. Then, Tianjin and Chengdu have relatively low resilience scores, but both are gradually transforming from low-resilience cities to moderately resilient ones. Further, the obstacle degree model shows that economic resilience and social resilience have the greatest impact on the resilience of smart cities. This paper provides a new perspective related to smart cities for subsequent urban resilience evaluation research. © ASCE.

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Analysis and Practice of Ideological and Political Education in computer Public Basic Courses in architecture univ.rsities Based on Machine Learning and Deep Learning 24

Analysis and Practice of Ideological and Political Education...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Education Digitalization and computer science, EDCS 2024

作者： Lv, Cheng Department of Computer Science School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China

ISBN: (纸本)9798400710360

In response to the shortcomings of ideological and political education in the computer basic course of our school, the teaching team has conducted in-depth research on the connotation of ideological and political education in the course, accurately grasped the direction of ideological and political education in the course, innovatively proposed the"progressive method of ideological and political education", and constructed an integrated curriculum system of ideological and political education in the course;Using Orange3 software and machine learning algorithms to deeply explore the ideological and political elements of the curriculum, constructing an analytical model, formulating personalized teaching and learning strategies, and constructing a double-layer teaching evaluation system that emphasizes both morality and ability. Through the analysis of course data, it is shown that the effectiveness of ideological and political education in the curriculum has been comprehensively improved, and the quality of teaching has been comprehensively enhanced. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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Course construction based on FD-QM standards and analysis and mining of course data 24

Course construction based on FD-QM standards and analysis an...

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2024 International Conference on Intelligent Education and computer Technology, IECT 2024

作者： Lv, Cheng Department of Computer Science School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China

ISBN: (纸本)9798400709920

In response to the shortcomings of the SPOC course "Introduction to Computational Thinking"at beijing univ.rsity of civil engineering and architecture, the teaching team has transformed and improved the course design and practice based on the existing High quality undergraduate courses in beijing univ.rsities and beijing Curriculum Ideological and Political Demonstration Course. We aim to maintain consistency and linkage in learning objectives, learning assessments, teaching materials, learning activities, and course technology under the principle of consistent construction. Learning objectives are clearer and more measurable;learning assessment is more scientific, diverse, and reliable;Curriculum resources can meet the needs of students at different levels and majors;learning activities can fully mobilize students' subjective initiative;Curriculum technology helps to achieve learning objectives, and can reflect the characteristics of the discipline, with univ.rsality and progressiveness. Through the construction and practice of the FD-QM standard, the course team has established the principles of course standardization, clarified the direction of course material construction, drawn a knowledge graph of course knowledge points, accurately grasped the degree of learning objectives, upgraded the "characteristic"teaching resource library, enhanced student interest, and integrated ideological and political education into the curriculum, ultimately achieving a comprehensive improvement in the quality of course teaching. © 2024 ACM.

关键词： Knowledge graph

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Signal Timing Optimization Model of Continuous-Flow Intersection in Connected Environment 24

Signal Timing Optimization Model of Continuous-Flow Intersec...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： He, Longxiang Kong, Dewen Zhao, Zilong Sun, Lishan Liu, Yue Faculty of Architecture Civil and Transportation Engineering Beijing Univ. of Technology China School of Transportation Science and Engineering Beihang Univ. Beijing Municipal Commission of Transport China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The special design form of main and minor intersections in continuous-flow intersections (CFI) brings challenges to signal timing optimization. Therefore, a transformation idea is proposed in this paper, that is, based on the spatiotemporal coordination relationship of traffic flow between main and minor intersections, the CFI is transformed into a conventional intersection, and then the signal timing optimization is performed, to simplify the difficulty of signal timing optimization of CFI. Firstly, based on the signal cooperation relationship between the main intersection and minor intersections of CFI, the transformation method from CFI to virtual conventional intersections is proposed. Then, we construct a signal time optimization algorithm, which solves the sequence of vehicles discharging from the intersection to minimize the total delay of vehicles to get the optimal signal time. Finally, simulation results show that the proposed method has good performance under different traffic demand levels, which can greatly reduce vehicle delay and improve intersection operation efficiency. © ASCE.

关键词： Vehicles

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WCM-WTrA: A Cross-Project Defect Prediction Method Based on Feature Selection and Distance-Weight Transfer Learning

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Chinese Journal of Electronics 2022年第2期31卷 354-366页

作者： LEI Tianwei XUE Jingfeng WANG Yong NIU Zequn SHI Zhiwei ZHANG Yu School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

Cross-project defect prediction is a hot topic in the field of defect prediction. How to reduce the difference between projects and make the model have better accuracy is the core problem. This paper starts from two perspectives: feature selection and distance-weight instance transfer. We reduce the differences between projects from the perspective of feature engineering and introduce the transfer learning technology to construct a cross-project defect prediction model WCM-WTrA and multi-source model Multi-WCM-WTrA. We have tested on AEEEM and ReLink datasets, and the results show that our method has an average improvement of 23%compared with TCA+ algorithm on AEEEM datasets,and an average improvement of 5% on ReLink datasets.

关键词： feature engineering cross-project defect prediction software defect prediction project management feature selection learning (artificial intelligence) software maintenance WCM-WTrA distance-weight transfer learning software quality distance-weight instance transfer multisource model MultiWCM-WTrA

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Real-Time Monitoring Track Local Irregularity of High-Speed Railway Based on SMVMD-PCA 3

Real-Time Monitoring Track Local Irregularity of High-Speed ...

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3rd International Conference on Rail Transportation, ICRT 2024

作者： Wang, Xiaohui Liu, Hai Yang, Jianwei School of Civil Engineering Guangzhou Univ. Guangzhou China Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles Beijing Univ. of Civil Engineering and Architecture Beijing China

ISBN: (数字)9780784485941

ISBN: (纸本)9780784485941

Ensuring the stability of high-speed railway tracks is crucial for safety. However, traditional methods that rely on track geometric parameter recombination suffer from hysteresis and inadaptability due to long detection time periods. To address this issue and enable real-time monitoring of track irregularities, this paper proposes a research framework based on the successive multivariate variational mode decomposition (SMVMD)-Spearman method. It analyzes the correlation between track irregularity and vehicle body acceleration (VBA) in the time-frequency domain, providing theoretical evidence for estimating track irregularity using VBA. Additionally, the successive multivariate variational mode decomposition-principal component analysis (SMVMD-PCA) method is introduced to estimate local track irregularity. It involves modal decomposition of multi-source data and employs PCA to transform modal data from linear correlation to linear independence. By integrating acceleration information into existing track geometric parameters, the method derives new geometric parameters. Evaluation on different cases demonstrates the effectiveness and accuracy of the proposed method in identifying track irregularities. This study contributes to the theoretical basis for on-site maintenance and provides valuable insights for ensuring the safety and stability of high-speed railway tracks. © ASCE.

关键词： Railroads

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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

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Frontiers of computer science 2024年第5期18卷 1-10页

作者： Lingling ZHAO Shitao SONG Pengyan WANG Chunyu WANG Junjie WANG Maozu GUO Faculty of Computing Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering Liaoning University of TechnologyJinzhou 121004China School of Computer Science Northeast Electric Power UniversityJilin 132000China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.

关键词： lithium-ion battery remaining useful life deep learning MLP-Mixer mixture-of-experts

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Research on the Application of Digital Construction Technology in the Field of Full Life-Cycle Project Management

Research on the Application of Digital Construction Technolo...

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2023 International Conference on Construction and Real Estate Management: The Human-Centered Construction Transformation, ICCREM 2023

作者： Liu, Xinyue Wan, Dongjun Su, Zhaopeng School of Economics and Management Engineering Beijing Univ. of Civil Engineering and Architecture Beijing China

ISBN: (数字)9780784485217

ISBN: (纸本)9780784485217

With the rapid development of digital information technology, the traditional construction industry has gradually transformed and upgraded, and the connection between digitization and construction industry has become closer. As a new construction mode, smart construction deeply integrates the new generation of information technology, which has become a research hotspot and has received extensive attention. As one of the most basic and important digital technologies, BIM plays an important role in the full life-cycle of construction and provides strong digital support for smart construction. This paper introduces the meaning and current situation of smart construction, discusses the application of digital technology in the field of smart construction, and puts forward suggestions for the future development of the construction industry. © ASCE.

关键词： Construction industry

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How to Determine Optimal Parking Prices under Uncertain Parking Demand 24

How to Determine Optimal Parking Prices under Uncertain Park...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Zhao, Pengfei Jiao, Pengpeng Li, Jianshi Song, Tiezheng Wang, Yuanyuan School of Civil and Transportation Engineering Beijing Univ. of Civil Engineering and Architecture Beijing China Beijing Static Traffic Investment and Operation Co. Ltd. China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

Reasonable parking fee pricing has become one of the most effective ways to address parking problems. We developed a new pricing model for uncertain parking demand distributions to maximize the expected revenue of the parking manager. Considering a uniform parking demand distribution, we derive the parking fee under supply and demand equilibrium and the expected parking demand under various parking fees. Furthermore, to maximize the parking management revenue, the theoretical optimal parking fee is deduced. Finally, numerical experiments verify the effectiveness of the model. The outcomes of this study furnish theoretical underpinnings that can bolster the pursuit of sustainable urban transportation development. © ASCE.

关键词： Parking

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