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The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management.
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Generative adversarial nets
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Synthetic drought scenario generation to support bottom-up water supply vulnerability assessments
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Variational inference & deep learning: A new synthesis
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Smart augmentation learning an optimal data augmentation strategy
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Evaluating transport externalities of urban growth: a critical review of scenario-based planning methods
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Attention is all you need
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A survey on the edge computing for the internet of things
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Zhu, J.Y., Park, T., Isola, P., Efros, A.A., 2017 · 2017
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Privacy preserving synthetic data release using deep learning, in: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I 18, Springer. pp. 510–526
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Artificial intelligence and smart cities
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Model-free renewable scenario generation using generative adversarial networks
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Edge computing framework for enabling situation awareness in iot based smart city
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Jiang, C., Mao, Y., Chai, Y., Yu, M., Tao, S., 2018 · 2018
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Prediction of short-term voltage instability using a digital faster than real-time replica, in: IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society, IEEE. pp. 3582–3587
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Frankengan: guided detail synthesis for building mass-models using style-synchonized gans
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A novel digital twin-centric approach for driver intention prediction and traffic congestion avoidance
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Edge computing architecture for mobile crowdsensing
Marjanović, M., Antonić, A., Žarko, I.P., 2018 · 2018
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Importance of scenario analysis in urban development for urban water infrastructure planning and management
Mikovits, C., Rauch, W., Kleidorfer, M., 2018 · 2018
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Enabling cognitive smart cities using big data and machine learning: Approaches and challenges
Mohammadi, M., Al-Fuqaha, A., 2018 · 2018
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Systematic review or scoping review? guidance for authors when choosing between a systematic or scoping review approach
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The value of 3d models and immersive technology in planning urban density, in: Proceedings of the 23rd International ACM Conference on 3D Web Technology, pp. 1–4
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On big data, artificial intelligence and smart cities
Allam, Z., Dhunny, Z.A., 2019 · 2019
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Digital twin, virtual reality and space syntax: Civic engagement and decision support for smart, sustainable cities, in: Proceedings of the 12th International Space Syntax Symposium, pp. 316–1
Dembski, F., Yamu, C., Wössner, U., 2019 · 2019
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Artificial intelligence for decision making in the era of big data–evolution, challenges and research agenda
Duan, Y., Edwards, J.S., Dwivedi, Y.K., 2019 · 2019
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A variational autoencoder based generative model of urban human mobility, in: 2019 IEEE conference on multimedia information processing and retrieval (MIPR), IEEE. pp. 425–430
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A digital twin approach for fault diagnosis in distributed photovoltaic systems
Jain, P., Poon, J., Singh, J.P., Spanos, C., Sanders, S.R., Panda, S.K., 2019 · 2019
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Foundations for building a digital twin for water utilities
Karmous-Edwards, G., Conejos, P., Mahinthakumar, K., Braman, S., Vicat-Blanc, P., Barba, J., 2019 · 2019
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Modelling urban networks using variational autoencoders
Kempinska, K., Murcio, R., 2019 · 2019
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Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks
Kosaraju, V., Sadeghian, A., Martín-Martín, R., Reid, I., Rezatofighi, H., Savarese, S., 2019 · 2019
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Migrating from monolithic architecture to microservices: A rapid review, in: 2019 38th International Conference of the Chilean Computer Science Society (SCCC), IEEE. pp. 1–7
Ponce, F., Márquez, G., Astudillo, H., 2019 · 2019
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Developing a dynamic digital twin at a building level: Using cambridge campus as case study, in: International Conference on Smart Infrastructure and Construction 2019 (ICSIC) Driving data-informed decision-making, ICE Publishing. pp. 67–75
Qiuchen Lu, V., Parlikad, A.K., Woodall, P., Ranasinghe, G.D., Heaton, J., 2019 · 2019
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Artificial intelligence-aided design: Smart design for sustainable city development
Quan, S.J., Park, J., Economou, A., Lee, S., 2019 · 2019
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The universal factory: Data production and platforms
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Scenario-based identification of key factors for smart cities development policies
Sokolov, A., Veselitskaya, N., Carabias, V., Yildirim, O., 2019 · 2019
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Supervised variational autoencoders for soft sensor modeling with missing data
Xie, R., Jan, N.M., Hao, K., Chen, L., Huang, B., 2019 · 2019
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Scenario forecasting of residential load profiles
Zhang, L., Zhang, B., 2019 · 2019
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Cognitwin–hybrid and cognitive digital twins for the process industry, in: 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), IEEE. pp. 1–8
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Abdollahi, A., Pradhan, B., Gite, S., Alamri, A., 2020 · 2020
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Explainable artificial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai
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3d building façade reconstruction using deep learning
Bacharidis, K., Sarri, F., Ragia, L., 2020 · 2020
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Covid-gan: Estimating human mobility responses to covid-19 pandemic through spatio-temporal conditional generative adversarial networks, in: Proceedings of the 28th international conference on advances in geographic information systems, pp. 273–282
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Building and exploiting a digital twin for the management of drinking water distribution networks
Conejos Fuertes, P., Martínez Alzamora, F., Hervás Carot, M., Alonso Campos, J., 2020 · 2020
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Smart grid anomaly detection using a deep learning digital twin, in: 2020 52nd North American Power Symposium (NAPS), IEEE. pp. 1–6
Danilczyk, W., Sun, Y.L., He, H., 2021 · 2020
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Using Generative Adversarial Networks to Classify Structural Damage Caused by Earthquakes
Delacruz, G.P., 2020 · 2020
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Urban digital twins for smart cities and citizens: The case study of herrenberg, germany
Dembski, F., Wössner, U., Letzgus, M., Ruddat, M., Yamu, C., 2020 · 2020
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Generation of driving scenario trajectories with generative adversarial networks, in: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), IEEE. pp. 1–6
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Smart city digital twin–enabled energy management: Toward real-time urban building energy benchmarking
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Overview of energy management and leakage control systems for smart water grids and digital water
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The comparison of microservice and monolithic architecture, in: 2020 IEEE XVIth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH), IEEE. pp. 150–153
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Artificial intelligence techniques for smart city applications, in: Proceedings of the 18th International Conference on Computing in Civil and Building Engineering: ICCCBE 2020, Springer. pp. 3–15
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