scholarly journals Agent-Based Modeling (ABM): Support for Emphasizing the Air Transport Infrastructure Dependence of Space Systems

2019 ◽  
Vol 11 (19) ◽  
pp. 5331 ◽  
Author(s):  
Olga Bucovetchi ◽  
Alexandru Georgescu ◽  
Dorel Badea ◽  
Radu D. Stanciu
Keyword(s):  
Critical Infrastructure ◽  
System Of Systems ◽  
Agent Based Modeling ◽  
Transport Infrastructure ◽  
Air Transport ◽  
Space Systems ◽  
Agent Based ◽  
Space Infrastructure ◽  
New Applications

Critical infrastructure is foundational for the prosperity and quality of life in any society. By definition, its destruction or disruption would cause severe damage and possibly loss of life. Within this understanding, space systems are a new category of critical infrastructure, emerging as an enabler of new applications which are critical within the wider system-of-systems. This paper presents the results of a modeling exercise validating the proof of concept regarding the idea of the global, air-transport-critical infrastructure’s dependence on space systems. By using an open-source application, the authors constructed a complex system made up of 18 airports for which six scenarios were modeled that represent either the exposure to specific space phenomena or the effects of a partial or total critical space infrastructure disruption. Despite the limitations and assumptions made in the building of this model, its results suggest that a significant impact would result from disruptive events, with the potential for cascading disruptions within the system, beyond the system under analysis, and into the wider system-of-systems. Tools such as this model are useful to policy- and decision-makers, not only to protect existing, critical infrastructures, but also to adequately source future risks, vulnerabilities, and threats, and design and build new infrastructures.

Agent-Based Modeling the Emergent Behavior of A System-of-Systems

2009 ◽  
Vol 19 (1) ◽  
pp. 1581-1590 ◽  
Author(s):  
John C. Hsu ◽  
John R. Clymer ◽  
Jose Garcia ◽  
Efrain Gonzalez
Keyword(s):  
System Of Systems ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Agent Based

Multilevel Agent-Based Modeling of System of Systems

2017 ◽  
Vol 11 (4) ◽  
pp. 2084-2095 ◽  
Author(s):  
Jean-Baptiste Soyez ◽  
Gildas Morvan ◽  
Rochdi Merzouki ◽  
Daniel Dupont
Keyword(s):  
System Of Systems ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Fuzzy Optimization of Acknowledged System of Systems Meta-architectures for Agent based Modeling of Development

2014 ◽  
Vol 28 ◽  
pp. 404-411 ◽  
Author(s):  
Louis Pape ◽  
Siddhartha Agarwal ◽  
Kristin Giammarco ◽  
Cihan Dagli
Keyword(s):  
Fuzzy Optimization ◽  
System Of Systems ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Simulation Approaches for System of Systems: Events-based versus Agent Based Modeling

2015 ◽  
Vol 44 ◽  
pp. 363-372 ◽  
Author(s):  
W. Clifton Baldwin ◽  
Brian Sauser ◽  
Robert Cloutier
Keyword(s):  
System Of Systems ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Impact Propagation in Airport Systems

2021 ◽  
pp. 191-206
Author(s):  
Corinna Köpke ◽  
Kushal Srivastava ◽  
Louis König ◽  
Natalie Miller ◽  
Mirjam Fehling-Kaschek ◽  
...  
Keyword(s):  
Critical Infrastructure ◽  
Transport Infrastructure ◽  
Test Case ◽  
Agent Based ◽  
Counter Measures ◽  
Physical Threat ◽  
Small Test ◽  
To Come ◽  
The Impact

AbstractThe effective protection of critical infrastructure against cyber and physical security threats involves many different steps from initially the identification of risks to finally the implementation of counter measures in the infrastructure. To derive counter measures and to come to intelligent decisions facing the identified risks, the impact calculation plays a central role. The impact of a specific threat can propagate through the systems of the infrastructure and thus needs to be analysed carefully. In this paper, the role of impact propagation of cyber-physical threats for infrastructure protection is discussed, exemplified for airport systems. In the ongoing EU-H2020 project SATIE (Security of Air Transport Infrastructure of Europe) a toolkit is developed containing two tools for impact propagation, namely the Business Impact Assessment (BIA) and the Impact Propagation Simulation (IPS). Both tools are described and for a small test case the propagation of a cyber threat and the transformation into a physical threat is demonstrated in a network representation as well as an agent-based model of the airport’s systems employing the IPS.

scholarly journals Modeling the Patients Flow Behavior in Hilla Emergency Departments

2018 ◽  
Vol 7 (4.19) ◽  
pp. 801
Author(s):  
Saad Talib Hasson ◽  
Rafalyasen Al-asadi
Keyword(s):  
Emergency Department ◽  
Flow Behavior ◽  
Evaluation Process ◽  
Agent Based Modeling ◽  
Discrete Events ◽  
Flexible Tool ◽  
Agent Based ◽  
Service Rates ◽  
Ed Operations

Emergency department (ED) represents a crucial and suitable for most patients' emergency cases at any time. It is extremely associated health services dedicated mostly to treat the arriving patient's with uncertain illnesses and without previousappointment.Patient flow sequences representa very complex processdue to the different uncertain requirements and different possible paths that patients may guide to complete their treatment.  An Agent Based Modeling (ABM) approach is implemented and appliedin an emergency department in Hilla hospital as a case studyin this paper.Thisstudy combinesABM with queuing and discrete events simulationas an evaluation process for the patients flow behavior and staff utilization in an emergency department. ABM is a flexible tool that can be created to imitatecertain complex environment. It can offer certain level of supports for managers to consider the relative influence of current or suggested strategies. It provides a suitablesituation in studying andpredicting the interactions and behavior's in ED operations. This study aims to maximize the patient's throughput, minimize their waitingtimesand optimize the resources utilization. The methodology that followed in this study is to estimate the optimal required number of ED staff's, which involves doctors, triage nurses, and receptionist, lab and x-raytechnician. Patients were modeled as agents having an ability to interact with others and with staffs and to select whether to wait and stay in the system or to leave at any stage of treatment. The simulation results is implemented according to the real collected data and the managers experiences about the averages of arrival and service rates with flow sequence probabilities. Waiting and idle times for the patients and staffs showed a good indication about the quality of services.   

scholarly journals Integrating agent-based modeling, serious gaming, and co-design for planning transport infrastructure and public spaces

2020 ◽  
Author(s):  
Liu Yang ◽  
Lufeng Zhang ◽  
Andreas Philippopoulos-Mihalopoulos ◽  
Emile J. L. Chappin ◽  
Koen H. van Dam
Keyword(s):  
Public Spaces ◽  
Agent Based Modeling ◽  
Transport Infrastructure ◽  
Serious Gaming ◽  
Agent Based
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