Critical flow centrality measures on interdependent networks with time-varying demands
This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation)...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Williams, James Bryan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study - 2012, IJCIP, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:35 ; year:2021 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.ijcip.2021.100462 |
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| 520 | |a This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. | ||
| 520 | |a This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. | ||
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10.1016/j.ijcip.2021.100462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001610.pica (DE-627)ELV056222564 (ELSEVIER)S1874-5482(21)00051-2 DE-627 ger DE-627 rakwb eng 610 VZ 670 VZ 35.80 bkl Williams, James Bryan verfasserin aut Critical flow centrality measures on interdependent networks with time-varying demands 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. Network reliability Elsevier Network dependencies Elsevier Centrality measures Elsevier Infrastructure reliability Elsevier Network science Elsevier Component importance measures Elsevier Enthalten in Elsevier 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study 2012 IJCIP Amsterdam [u.a.] (DE-627)ELV016099079 volume:35 year:2021 pages:0 https://doi.org/10.1016/j.ijcip.2021.100462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.80 Makromolekulare Chemie VZ AR 35 2021 0 |
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10.1016/j.ijcip.2021.100462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001610.pica (DE-627)ELV056222564 (ELSEVIER)S1874-5482(21)00051-2 DE-627 ger DE-627 rakwb eng 610 VZ 670 VZ 35.80 bkl Williams, James Bryan verfasserin aut Critical flow centrality measures on interdependent networks with time-varying demands 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. Network reliability Elsevier Network dependencies Elsevier Centrality measures Elsevier Infrastructure reliability Elsevier Network science Elsevier Component importance measures Elsevier Enthalten in Elsevier 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study 2012 IJCIP Amsterdam [u.a.] (DE-627)ELV016099079 volume:35 year:2021 pages:0 https://doi.org/10.1016/j.ijcip.2021.100462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.80 Makromolekulare Chemie VZ AR 35 2021 0 |
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10.1016/j.ijcip.2021.100462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001610.pica (DE-627)ELV056222564 (ELSEVIER)S1874-5482(21)00051-2 DE-627 ger DE-627 rakwb eng 610 VZ 670 VZ 35.80 bkl Williams, James Bryan verfasserin aut Critical flow centrality measures on interdependent networks with time-varying demands 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. Network reliability Elsevier Network dependencies Elsevier Centrality measures Elsevier Infrastructure reliability Elsevier Network science Elsevier Component importance measures Elsevier Enthalten in Elsevier 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study 2012 IJCIP Amsterdam [u.a.] (DE-627)ELV016099079 volume:35 year:2021 pages:0 https://doi.org/10.1016/j.ijcip.2021.100462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.80 Makromolekulare Chemie VZ AR 35 2021 0 |
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Enthalten in 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study Amsterdam [u.a.] volume:35 year:2021 pages:0 |
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Enthalten in 70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study Amsterdam [u.a.] volume:35 year:2021 pages:0 |
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70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study |
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70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study |
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Critical flow centrality measures on interdependent networks with time-varying demands |
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70 Delirium in elderly patients hospitalized and undergoing urologic surgery. Incidence and predictive role of Multidimensional Geriatric Evaluation (MGE) to define a high-risk population and prevent complications: Results of a prospective study |
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critical flow centrality measures on interdependent networks with time-varying demands |
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Critical flow centrality measures on interdependent networks with time-varying demands |
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This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. |
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This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. |
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This paper presents a method that allows urban planners and municipal engineers to identify critical components of interdependent infrastructure systems. The intent of the method is to provide a means of modeling the impact of capacity-related changes (e.g., population growth, component degradation) on a city’s ability to deliver resources to critical locations. Infrastructure systems are modeled as flow networks in which capacities, demands, and supply constraints vary over time; demand nodes also have criticality ratings that allow a user to model levels of importance. Interconnections between infrastructure systems are represented by physical and geospatial dependencies at a component level. A flow-based centrality measure is used to rank components according to their role in the delivery of resources to critical locations. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains interconnected water and electricity networks. Finally, two forms of reliability analysis are demonstrated: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis. |
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