A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems
As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system model...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhu, Feng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Umfang: |
16 |
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| Übergeordnetes Werk: |
Enthalten in: Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry - Christopoulos, Georgios ELSEVIER, 2014, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:77 ; year:2017 ; pages:141-156 ; extent:16 |
| Links: |
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| DOI / URN: |
10.1016/j.simpat.2017.05.010 |
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ELV030369126 |
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| 520 | |a As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. | ||
| 520 | |a As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. | ||
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10.1016/j.simpat.2017.05.010 doi GBVA2017006000030.pica (DE-627)ELV030369126 (ELSEVIER)S1569-190X(17)30092-8 DE-627 ger DE-627 rakwb eng 530 510 530 DE-600 510 DE-600 610 VZ 600 540 VZ Zhu, Feng verfasserin aut A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems 2017transfer abstract 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. Yao, Yiping oth Tang, Wenjie oth Tang, Jun oth Enthalten in Elsevier Science Christopoulos, Georgios ELSEVIER Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry 2014 Amsterdam [u.a.] (DE-627)ELV017600162 volume:77 year:2017 pages:141-156 extent:16 https://doi.org/10.1016/j.simpat.2017.05.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_70 AR 77 2017 141-156 16 045F 530 |
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10.1016/j.simpat.2017.05.010 doi GBVA2017006000030.pica (DE-627)ELV030369126 (ELSEVIER)S1569-190X(17)30092-8 DE-627 ger DE-627 rakwb eng 530 510 530 DE-600 510 DE-600 610 VZ 600 540 VZ Zhu, Feng verfasserin aut A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems 2017transfer abstract 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. Yao, Yiping oth Tang, Wenjie oth Tang, Jun oth Enthalten in Elsevier Science Christopoulos, Georgios ELSEVIER Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry 2014 Amsterdam [u.a.] (DE-627)ELV017600162 volume:77 year:2017 pages:141-156 extent:16 https://doi.org/10.1016/j.simpat.2017.05.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_70 AR 77 2017 141-156 16 045F 530 |
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10.1016/j.simpat.2017.05.010 doi GBVA2017006000030.pica (DE-627)ELV030369126 (ELSEVIER)S1569-190X(17)30092-8 DE-627 ger DE-627 rakwb eng 530 510 530 DE-600 510 DE-600 610 VZ 600 540 VZ Zhu, Feng verfasserin aut A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems 2017transfer abstract 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. Yao, Yiping oth Tang, Wenjie oth Tang, Jun oth Enthalten in Elsevier Science Christopoulos, Georgios ELSEVIER Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry 2014 Amsterdam [u.a.] (DE-627)ELV017600162 volume:77 year:2017 pages:141-156 extent:16 https://doi.org/10.1016/j.simpat.2017.05.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_70 AR 77 2017 141-156 16 045F 530 |
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10.1016/j.simpat.2017.05.010 doi GBVA2017006000030.pica (DE-627)ELV030369126 (ELSEVIER)S1569-190X(17)30092-8 DE-627 ger DE-627 rakwb eng 530 510 530 DE-600 510 DE-600 610 VZ 600 540 VZ Zhu, Feng verfasserin aut A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems 2017transfer abstract 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. Yao, Yiping oth Tang, Wenjie oth Tang, Jun oth Enthalten in Elsevier Science Christopoulos, Georgios ELSEVIER Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry 2014 Amsterdam [u.a.] (DE-627)ELV017600162 volume:77 year:2017 pages:141-156 extent:16 https://doi.org/10.1016/j.simpat.2017.05.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_70 AR 77 2017 141-156 16 045F 530 |
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10.1016/j.simpat.2017.05.010 doi GBVA2017006000030.pica (DE-627)ELV030369126 (ELSEVIER)S1569-190X(17)30092-8 DE-627 ger DE-627 rakwb eng 530 510 530 DE-600 510 DE-600 610 VZ 600 540 VZ Zhu, Feng verfasserin aut A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems 2017transfer abstract 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. Yao, Yiping oth Tang, Wenjie oth Tang, Jun oth Enthalten in Elsevier Science Christopoulos, Georgios ELSEVIER Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry 2014 Amsterdam [u.a.] (DE-627)ELV017600162 volume:77 year:2017 pages:141-156 extent:16 https://doi.org/10.1016/j.simpat.2017.05.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_70 AR 77 2017 141-156 16 045F 530 |
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Enthalten in Percutaneous Intervention of Circumflex Chronic Total Occlusions Is Associated With Worse Procedural Outcomes: Insights From a Multicentre US Registry Amsterdam [u.a.] volume:77 year:2017 pages:141-156 extent:16 |
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Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. 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A hierarchical composite framework of parallel discrete event simulation for modelling complex adaptive systems |
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As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. |
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As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. |
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As complex adaptive systems(CAS) continue to grow in scale and complexity, and the need for system adaptability increases, systems modelling has become an essential concern. Parallel discrete event simulation became a preferred choice as logical process world view, which bridges complex system modelling and high-performance computing. To resolve the shortcoming of this world view identified with respect to modularity and scalability. A hierarchical composite modelling framework was proposed, which is a three-level architecture intended to support the composition and integration of sub-models. The bottom layer is simulation model component(SMC), which is not a model but implement some simulation-specific support functionality. The middle layer is logical process model(LP), which describes an agent which can react to the current situation by executing a sequence of SMCs. The top layer is CAS system model, which defines a CAS model consist of several LPs and also the interactions between these LPs. The hierarchical composite modelling process and parallel simulation execution strategy are discussed to support the modelling and simulation of a CAS. In order to verify its effectiveness, a complex social opinion system model is proposed based on this hierarchical composite modelling framework. The experimental results confirms the viability of utilizing multi-level architecture for simulating large scale complex adaptive systems. |
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