435 lines
22 KiB
BibTeX
435 lines
22 KiB
BibTeX
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@misc{ref0,
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author = {},
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title = {The Lockheed Martin Aeronautics Win – Integration and Digital Twins the Secret to Siemens’ A\&D Success},
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howpublished = {\url{http://plm-erpnews.se/aktuellt-pa-engineering-com-the-lockheed-martin-win-integration-is-the-secret-to-siemens-success-in-aerospace-defense-meet-vp-dale-tutt/}}
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}
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@misc{ref1,
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author = {},
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title = {aircraft-performance-engineering},
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howpublished = {\url{https://www.plm.automation.siemens.com/global/fr/industries/aerospace-defense/aircrafts-airframes/aircraft-performance-engineering.html}}
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}
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@misc{refu1,
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author = {},
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title = {中国智能制造十大科技进展},
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howpublished = {\url{https://icim.org.cn/news/219.html}}
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}
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@article{ref2,
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title={产品数字孪生体的内涵,体系结构及其发展趋势},
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author={庄存波 and 刘检华 and 熊辉 and 丁晓宇 and 刘少丽 and 瓮刚},
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journal={计算机集成制造系统},
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volume={23},
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number={4},
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pages={16},
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year={2017},
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}
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@inbook{ref3,
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abstract = {Systems do not simply pop into existence. They progress through lifecycle phases of creation, production, operations, and disposal. The issues leading to undesirable and unpredicted emergent behavior are set in place during the phases of creation and production and realized during the operational phase, with many of those problematic issues due to human interaction. We propose that the idea of the Digital Twin, which links the physical system with its virtual equivalent can mitigate these problematic issues. We describe the Digital Twin concept and its development, show how it applies across the product lifecycle in defining and understanding system behavior, and define tests to evaluate how we are progressing. We discuss how the Digital Twin relates to Systems Engineering and how it can address the human interactions that lead to ``normal accidents.'' We address both Digital Twin obstacles and opportunities, such as system replication and front running. We finish with NASA's current work with the Digital Twin.},
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address = {Cham},
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author = {Grieves, Michael and Vickers, John},
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booktitle = {Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches},
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doi = {10.1007/978-3-319-38756-7_4},
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editor = {Kahlen, Franz-Josef and Flumerfelt, Shannon and Alves, Anabela},
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isbn = {978-3-319-38756-7},
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pages = {85--113},
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publisher = {Springer International Publishing},
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title = {Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems},
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url = {https://doi.org/10.1007/978-3-319-38756-7_4},
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year = {2017},
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bdsk-url-1 = {https://doi.org/10.1007/978-3-319-38756-7_4}
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}
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@misc{agrawal2022digital,
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title={Digital Twin: From Concept to Practice},
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author={Ashwin Agrawal and Martin Fischer and Vishal Singh},
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year={2022},
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eprint={2201.06912},
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archivePrefix={arXiv},
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primaryClass={cs.SE}
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}
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@inproceedings{ref4,
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title={The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles},
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author={ Glaessgen, E. and Stargel, D. },
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booktitle={Aiaa/asme/asce/ahs/asc Structures, Structural Dynamics ; Materials Conference Aiaa/asme/ahs Adaptive Structures Conference Aiaa},
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year={2012},
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abstract={Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation. Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements. To address the shortcomings of conventional approaches, a fundamental paradigm shift is needed. This paradigm shift, the Digital Twin, integrates ultra-high fidelity simulation with the vehicle's on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to mirror the life of its flying twin and enable unprecedented levels of safety and reliability.},
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}
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@article{ref5,
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title={About The Importance of Autonomy and Digital Twins for the Future of Manufacturing},
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author={ Rosen, R. and Wichert, G Von and Lo, G. and Bettenhausen, K. D. },
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journal={IFAC-PapersOnLine},
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volume={48},
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number={3},
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pages={567-572},
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year={2015},
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}
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@inproceedings{ref6,
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title={Digital Twin in manufacturing: A categorical literature review and classification},
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author={ Kritzinger, W. and Karner, M. and Traar, G. and Henjes, J. and Sihn, W. },
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pages={1016-1022},
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year={2018},
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}
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@article{ref7,
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title={The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0},
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author={ Uhlemann, H. J. and Lehmann, C. and Steinhilper, R. },
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journal={Procedia CIRP},
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volume={61},
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pages={335-340},
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year={2017},
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}
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@inbook{ref8,
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abstract = {The vision of the Digital Twin itself refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in all---the current and subsequent---lifecycle phases. In this chapter we focus on the simulation aspects of the Digital Twin. Today, modelling and simulation is a standard process in system development, e.g. to support design tasks or to validate system properties. During operation and for service first simulation-based solutions are realized for optimized operations and failure prediction. In this sense, simulation merges the physical and virtual world in all life cycle phases. Current practice already enables the users (designer, SW/HW developers, test engineers, operators, maintenance personnel, etc) to master the complexity of mechatronic systems.},
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address = {Cham},
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author = {Boschert, Stefan and Rosen, Roland},
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booktitle = {Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and their Designers},
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doi = {10.1007/978-3-319-32156-1_5},
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editor = {Hehenberger, Peter and Bradley, David},
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isbn = {978-3-319-32156-1},
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pages = {59--74},
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publisher = {Springer International Publishing},
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title = {Digital Twin---The Simulation Aspect},
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url = {https://doi.org/10.1007/978-3-319-32156-1_5},
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year = {2016},
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bdsk-url-1 = {https://doi.org/10.1007/978-3-319-32156-1_5}
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}
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@article{ref9,
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title={About The Importance of Autonomy and Digital Twins for the Future of Manufacturing},
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author={ Rosen, R. and Wichert, G Von and Lo, G. and Bettenhausen, K. D. },
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journal={IFAC-PapersOnLine},
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volume={48},
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number={3},
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pages={567-572},
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year={2015},
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}
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@article{ref10,
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title={Shaping the digital twin for design and production engineering},
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author={Anwer and Nabil and Schleich and Benjamin and Mathieu and Luc and Wartzack and Sandro},
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journal={CIRP Annals},
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year={2017},
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}
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@article{ref11,
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title={Machine Learning for Predictive Maintenance: A Multiple Classifier Approach},
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author={ Susto, G. A. and Schirru, A. and Pampuri, S. and Mcloone, S. and Beghi, A. },
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journal={IEEE transactions on industrial informatics},
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volume={11},
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number={3},
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pages={812-820},
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year={2015},
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}
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@article{ref12,
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title={Review of digital twin applications in manufacturing},
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author={ Cimino, Efl },
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journal={Computers in Industry},
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volume={113},
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year={2019},
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}
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@INPROCEEDINGS{ref13,
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author={Liu, Xuan and Luo, Ying},
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booktitle={2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)},
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title={Analytical Design of Optimal Fractional Order PID Control for Industrial Robot based on Digital Twin},
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year={2022},
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volume={},
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number={},
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pages={1-6},
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doi={10.1109/DTPI55838.2022.9998968}
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}
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@article{ref14,
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title={Digital Twin: Manufacturing Excellence through Virtual Factory Replication},
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author={ Grieves, M. },
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year={2015},
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}
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@article{ref15,
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title={Reengineering Aircraft Structural Life Prediction Using a Digital Twin},
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author={ Tuegel, E. J. and Ingraffea, A. R. and Eason, T. G. and Spottswood, S. M. },
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journal={International Journal of Aerospace Engineering},
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volume={2011},
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number={1687-5966},
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year={2011},
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abstract={Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail.},
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}
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@article{ref16,
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abstract = {Various kinds of engineering software and digitalized equipment are widely applied through the lifecycle of industrial products. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on theoretical and static model has been a conventional and powerful tool for the verification, validation, and optimization of a system in its early planning stage, but no attention is paid to the simulation application during system run-time. With the development of new-generation information and digitalization technologies, more data can be collected, and it is time to find a way for the deep application of all these data. As a result, the concept of digital twin has aroused much concern and is developing rapidly. Dispute and discussions around concepts, paradigms, frameworks, applications, and technologies of digital twin are on the rise both in academic and industrial communities. After a complete search of several databases and careful selection according to the proposed criteria, 240 academic publications about digital twin are identified and classified. This paper conducts a comprehensive and in-depth review of these literatures to analyze digital twin from the perspective of concepts, technologies, and industrial applications. Research status, evolution of the concept, key enabling technologies of three aspects, and fifteen kinds of industrial applications in respective lifecycle phase are demonstrated in detail. Based on this, observations and future work recommendations for digital twin research are presented in the form of different lifecycle phases.},
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author = {Mengnan Liu and Shuiliang Fang and Huiyue Dong and Cunzhi Xu},
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doi = {https://doi.org/10.1016/j.jmsy.2020.06.017},
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issn = {0278-6125},
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journal = {Journal of Manufacturing Systems},
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keywords = {Digital twin, Product lifecycle, Simulation, Industrial application, Literature review},
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note = {Digital Twin towards Smart Manufacturing and Industry 4.0},
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pages = {346-361},
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title = {Review of digital twin about concepts, technologies, and industrial applications},
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url = {https://www.sciencedirect.com/science/article/pii/S0278612520301072},
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volume = {58},
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year = {2021},
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bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0278612520301072},
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bdsk-url-2 = {https://doi.org/10.1016/j.jmsy.2020.06.017}
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}
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@article{ref17,
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abstract = {The digital twin is an emerging and vital technology for digital transformation and intelligent upgrade. Driven by data and model, the digital twin can perform monitoring, simulation, prediction, optimization, and so on. Specifically, the digital twin modeling is the core for accurate portrayal of the physical entity, which enables the digital twin to deliver the functional services and satisfy the application requirements. Therefore, this paper provides systematic research of current studies on the digital twin modeling. Since the digital twin model is a faithful reflection of the digital twin modeling performance, a comprehensive and insightful analysis of digital twin models is given first from the perspective of the application field, hierarchy, discipline, dimension, universality, and functionality. Based on the analysis of digital twin models, current studies on the digital twin modeling are classified and analyzed according to the six modeling aspects within the digital twin modeling theoretical system proposed in our previous work. Meanwhile, enabling technologies and tools for the digital twin modeling are investigated and summarized. Finally, observations and future research recommendations are presented.},
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author = {Fei Tao and Bin Xiao and Qinglin Qi and Jiangfeng Cheng and Ping Ji},
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doi = {https://doi.org/10.1016/j.jmsy.2022.06.015},
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issn = {0278-6125},
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journal = {Journal of Manufacturing Systems},
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keywords = {Digital twin, Digital twin modeling, Digital twin model, Enabling technologies, Enabling tools},
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pages = {372-389},
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title = {Digital twin modeling},
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url = {https://www.sciencedirect.com/science/article/pii/S0278612522001108},
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volume = {64},
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year = {2022},
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bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0278612522001108},
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bdsk-url-2 = {https://doi.org/10.1016/j.jmsy.2022.06.015}
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}
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@article{ref18,
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title={Sensor data transmission from a physical twin to a digital twin},
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author={Ala-Laurinaho, Riku and others},
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year={2019}
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}
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@book{ref19,
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title={Forecasting: principles and practice},
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author={Hyndman, Rob J and Athanasopoulos, George},
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year={2018},
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publisher={OTexts}
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}
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@article{ref20,
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title={Forecasting: theory and practice},
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author={Petropoulos, Fotios and Apiletti, Daniele and Assimakopoulos, Vassilios and Babai, Mohamed Zied and Barrow, Devon K and Taieb, Souhaib Ben and Bergmeir, Christoph and Bessa, Ricardo J and Bijak, Jakub and Boylan, John E and others},
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journal={International Journal of Forecasting},
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year={2022},
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publisher={Elsevier}
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}
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@article{ref21,
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title={Forecasting with big data: A review},
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author={Hassani, Hossein and Silva, Emmanuel Sirimal},
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journal={Annals of Data Science},
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volume={2},
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pages={5--19},
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year={2015},
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publisher={Springer}
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}
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@book{ref22,
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title={Nonlinear systems analysis},
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author={Vidyasagar, Mathukumalli},
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year={2002},
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publisher={SIAM}
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}
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@book{ref23,
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title={Time series analysis by state space methods},
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author={Durbin, James and Koopman, Siem Jan},
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volume={38},
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year={2012},
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publisher={OUP Oxford}
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}
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@article{ref24,
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title={Supply chain decision support systems based on a novel hierarchical forecasting approach},
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author={Villegas, Marco A and Pedregal, Diego J},
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journal={Decision Support Systems},
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volume={114},
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pages={29--36},
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year={2018},
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publisher={Elsevier}
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}
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@article{ref25,
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title={Time series forecasting of COVID-19 transmission in Canada using LSTM networks},
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author={Chimmula, Vinay Kumar Reddy and Zhang, Lei},
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journal={Chaos, Solitons \& Fractals},
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volume={135},
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pages={109864},
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year={2020},
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publisher={Elsevier}
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}
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@inproceedings{ref26,
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title={Show and tell: A neural image caption generator},
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author={Vinyals, Oriol and Toshev, Alexander and Bengio, Samy and Erhan, Dumitru},
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booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
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pages={3156--3164},
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year={2015}
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}
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@article{ref27,
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title={A review and taxonomy of wind and solar energy forecasting methods based on deep learning},
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author={Alkhayat, Ghadah and Mehmood, Rashid},
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journal={Energy and AI},
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volume={4},
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pages={100060},
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year={2021},
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publisher={Elsevier}
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}
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@article{ref28,
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title={Scheduling Sporadic and Aperiodic Events in a Hard Real-Time System},
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author={ Sprunt, B. and Sha, L. and Lehoczky, J. },
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year={1989},
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abstract={A real-time system consists of both aperiodic and periodic tasks. Periodic tasks have regular arrival times and hard deadlines. Aperiodic tasks have irregular arrival times and either soft or hard deadlines. This paper, we presents a new algorithm, the Sporadic Server algorithm, that greatly improves response times for soft-deadline aperiodic tasks and can guarantee hard deadlines for both periodic and aperiodic tasks. The operation of the Sporadic Server algorithm, its performance, and schedulability analysis are discussed and compared with previous, published aperiodic service algorithms. Real-time systems are used to control physical processes that range in complexity from automobile ignition systems to controllers for flight systems and nuclear power plants. In these systems, the correctness of system functions depends upon not only the results of computation but also the times at which results are produced.},
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}
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@article{ref29,
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title={Decentralized Decision-Making for Task Reallocation in a Hard Real-Time System},
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author={ Stankovic, J. A. },
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journal={IEEE Computer Society},
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year={1989},
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abstract={Summary: A decentralized task reallocation algorithm for hard real-time systems is developed and analyzed. The algorithm, which is fast and reliable, specifically considers deadlines of tasks, attempts to utilize all the nodes of a distributed system to achieve its objective, handles tasks in priority order, and separates policy and mechanism. An extensive performance analysis of the algorithm by means of simulation shows that it is quite effective in performing reallocations and that it is significantly better than a centralized approach.},
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}
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@article{ref30,
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title={A comparative study and analysis of time series forecasting techniques},
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author={Athiyarath, Srihari and Paul, Mousumi and Krishnaswamy, Srivatsa},
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journal={SN Computer Science},
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volume={1},
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number={3},
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pages={175},
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year={2020},
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publisher={Springer}
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}
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@book{ref31,
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title={Introduction to time series analysis and forecasting},
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author={Montgomery, Douglas C and Jennings, Cheryl L and Kulahci, Murat},
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year={2015},
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publisher={John Wiley \& Sons}
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}
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title={Nonstationary time series transformation methods: An experimental review},
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author={Salles, Rebecca and Belloze, Kele and Porto, Fabio and Gonzalez, Pedro H and Ogasawara, Eduardo},
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journal={Knowledge-Based Systems},
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volume={164},
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pages={274--291},
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year={2019},
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publisher={Elsevier}
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}
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title={A new approach for chaotic time series prediction using recurrent neural network},
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author={Li, Qinghai and Lin, Rui-Chang},
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journal={Mathematical Problems in Engineering},
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volume={2016},
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year={2016},
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publisher={Hindawi}
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}
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title={Predicting chaotic time series},
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author={Farmer, J Doyne and Sidorowich, John J},
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journal={Physical review letters},
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volume={59},
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number={8},
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pages={845},
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year={1987},
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publisher={APS}
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}
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title={Chaotic time series analysis},
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author={Liu, Zonghua},
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journal={Mathematical Problems in Engineering},
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volume={2010},
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year={2010},
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publisher={Hindawi}
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}
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title={A review of recurrent neural networks: LSTM cells and network architectures},
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author={Yu, Yong and Si, Xiaosheng and Hu, Changhua and Zhang, Jianxun},
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journal={Neural computation},
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volume={31},
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number={7},
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pages={1235--1270},
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year={2019},
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publisher={MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…}
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}
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@article{ref37,
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author = {Pfenning, F. and Elliott, C.},
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title = {Higher-Order Abstract Syntax},
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year = {1988},
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issue_date = {July 1988},
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publisher = {Association for Computing Machinery},
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address = {New York, NY, USA},
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volume = {23},
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number = {7},
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issn = {0362-1340},
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||
url = {https://doi.org/10.1145/960116.54010},
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||
doi = {10.1145/960116.54010},
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||
abstract = {We describe motivation, design, use, and implementation of higher-order abstract syntax as a central representation for programs, formulas, rules, and other syntactic objects in program manipulation and other formal systems where matching and substitution or unification are central operations. Higher-order abstract syntax incorporates name binding information in a uniform and language generic way. Thus it acts as a powerful link integrating diverse tools in such formal environments. We have implemented higher-order abstract syntax, a supporting matching and unification algorithm, and some clients in Common Lisp in the framework of the Ergo project at Carnegie Mellon University.},
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journal = {SIGPLAN Not.},
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month = {jun},
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pages = {199–208},
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numpages = {10}
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}
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@inproceedings{ref38,
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||
abstract = {A large variety of computing systems, such as compilers, interpreters, static analyzers, and theorem provers, need to manipulate syntactic objects like programs, types, formulas, and proofs. A common characteristic of these syntactic objects is that they contain variable binders, such as quantifiers, formal parameters, and blocks. It is a common observation that representing such binders using only first-order expressions is problematic since the notions of bound variable names, free and bound occurrences, equality up to alpha-conversion, substitution, etc., are not addressed naturally by the structure of first-order terms (labeled trees). This overview describes a higher-level and more declarative approach to representing syntax within such computational systems. In particular, we shall focus on a representation of syntax called higher-order abstract syntax and on a more primitive version of that representation called $\lambda$-tree syntax.},
|
||
address = {Berlin, Heidelberg},
|
||
author = {Miller, Dale},
|
||
booktitle = {Computational Logic --- CL 2000},
|
||
editor = {Lloyd, John and Dahl, Veronica and Furbach, Ulrich and Kerber, Manfred and Lau, Kung-Kiu and Palamidessi, Catuscia and Pereira, Lu{\'\i}s Moniz and Sagiv, Yehoshua and Stuckey, Peter J.},
|
||
isbn = {978-3-540-44957-7},
|
||
pages = {239--253},
|
||
publisher = {Springer Berlin Heidelberg},
|
||
title = {Abstract Syntax for Variable Binders: An Overview},
|
||
year = {2000}
|
||
}
|
||
|
||
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|
||
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|
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author={Kasprzyk, Dennis Michael and Drury, Colin G and Bialas, Wayne F},
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|
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@article{ref40,
|
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title={Reverse polish notation method},
|
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author={Krtolica, Predrag V and Stanimirovi{\'c}, Predrag S},
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journal={International Journal of Computer Mathematics},
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volume={81},
|
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number={3},
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pages={273--284},
|
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year={2004},
|
||
publisher={Taylor \& Francis}
|
||
}
|