A Methodology for Simulating Synthetic Populations for the Analysis of Socio-technical Infrastructures

Dam, Koen H. van; Bustos-Turu, Gonzalo; Shah, Nilay

doi:10.1007/978-3-319-47253-9_39

Cited by 8 publications

(12 citation statements)

References 3 publications

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“…In addition, the composition of the population and its characteristics, behaviour and interactions can be modelled to complete the representation of the social environment. To do so, the synthetic population of agents utilises synthetic social networks, allowing synthetic daily activities to be generated based on real population data [97,112]. There are several techniques that can be used to generate a synthetic population, including deterministic reweighting, conditional probability (Monte Carlo Simulation) and simulated annealing [113].…”

Section: Modelling Type and Methodsmentioning

confidence: 99%

“…Developing a simulation in which the outcomes rely on individual behaviour needs a synthetic population of human agents in which the heterogeneity of the agents' characteristics is consistent with the aggregate of characteristics of the real population [112]. Especially for spatially realistic simulation purposes, these population characteristics should be similar to real conditions in terms of socio-demographic attributes as well as spatial distribution [130].…”

Section: Agent Population Generationmentioning

confidence: 99%

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A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

Jumadi

Carver

Quincey

2017

Systems

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The understanding of evacuation processes is important for improving the effectiveness of evacuation plans in the event of volcanic disasters. In terms of social processes, the enactment of evacuations in volcanic crises depends on the variability of individual/household responses. This variability of population response is related to the uncertainty and unpredictability of the hazard characteristics of volcanoes-specifically, the exact moment at which the eruption occurs (temporal), the magnitude of the eruption and which locations are impacted (spatial). In order to provide enhanced evacuation planning, it is important to recognise the potential problems that emerge during evacuation processes due to such variability. Evacuation simulations are one approach to understanding these processes. However, experimenting with volcanic evacuations in the real world is risky and challenging, and so an agent-based model is proposed to simulate volcanic evacuation. This paper highlights the literature gap for this topic and provides the conceptual design for a simulation using an agent-based model. As an implementation, an initial evacuation model is presented for Mount Merapi in Indonesia, together with potential applications of the model for supporting volcanic evacuation management, discussion of the initial outcomes and suggestions for future work.

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Section: Modelling Type and Methodsmentioning

confidence: 99%

Section: Agent Population Generationmentioning

confidence: 99%

A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

Jumadi

Carver

Quincey

2017

Systems

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“…However, population microdata is commonly lacking in spatial representation details of household location due to confidentiality issues [120]. Moreover, the aggregate characteristics of human agents need to be consistent with the aggregate characteristics of the real population [121]. This population characteristic should be similar to the real situation regarding socio-demographic attributes as well as spatial distribution [122].…”

Section: Population and Synthetic Population Generationmentioning

confidence: 99%

Modelling Individual Evacuation Decisions during Natural Disasters: A Case Study of Volcanic Crisis in Merapi, Indonesia

et al. 2018

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As the size of human populations increases, so does the severity of the impacts of natural disasters. This is partly because more people are now occupying areas which are susceptible to hazardous natural events, hence, evacuation is needed when such events occur. Evacuation can be the most important action to minimise the impact of any disaster, but in many cases there are always people who are reluctant to leave. This paper describes an agent-based model (ABM) of evacuation decisions, focusing on the emergence of reluctant people in times of crisis and using Merapi, Indonesia as a case study. The individual evacuation decision model is influenced by several factors formulated from a literature review and survey. We categorised the factors influencing evacuation decisions into two opposing forces, namely, the driving factors to leave (evacuate) versus those to stay, to formulate the model. The evacuation decision (to stay/leave) of an agent is based on an evaluation of the strength of these driving factors using threshold-based rules. This ABM was utilised with a synthetic population from census microdata, in which everyone is characterised by the decision rule. Three scenarios with varying parameters are examined to calibrate the model. Validations were conducted using a retrodictive approach by performing spatial and temporal comparisons between the outputs of simulation and the real data. We present the results of the simulations and discuss the outcomes to conclude with the most plausible scenario. of 30year, Indonesia was the fourth most frequently affected Asian country [4]. Among the various natural hazards, volcanic eruptions pose a significant threat to Indonesia, as it is located within the "Ring of Fire" [5]. Merapi is the most active volcano in Indonesia, and the 2010 eruption was ranked third in the world since 2005 in terms of impact [4]. Being in such susceptible areas, people living close to Merapi should, therefore, develop their awareness and preparedness to evacuate when a hazard occurs.Evacuation is an important life-saving action in any disaster [6], with a history as old as human history in saving lives from natural disasters [7]. It takes place by moving people from a hazardous area to a safer place in a very limited time [8]. This time limit depends on the speed of the onset of the hazard. Some hazards occur rapidly, with others more slowly [1,9]. For example, hurricanes or earthquakes happen very quickly, while global temperature variations, rises in sea level, drought, and disease affect society more slowly [9]. For fast-onset hazards, immediate responses leading to evacuation are needed, because being at the wrong place at the wrong time will quickly lead to fatalities. Volcanic eruptions can happen several days after the initial signs of instability, but it is also possible for them to happen several weeks later [10]. Therefore, immediate responses from the surrounding population are needed, but there are often cases of people who refuse, or are reluctant to evacuate from hazardous are...

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“…For each zone, an heterogeneous group of agents is generated using a synthetic population methodology [18]. Each agent is then associated with a different activity schedule, level of car ownership, working status, etc.…”

Section: Modelling Frameworkmentioning

confidence: 99%

Simulating residential electricity and heat demand in urban areas using an agent-based modelling approach

Bustos-Turu

Dam

Acha

et al. 2016

2016 IEEE International Energy Conference (ENERGYCON)

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Abstract-Cities account for around 75% of the global energy demand and are responsible for 60-70% of the global greenhouse gasses emissions. To reduce this environmental impact it is important to design efficient energy infrastructures able to deal with high level of renewable energy resources. A crucial element in this design is the quantitative understanding of the dynamics behind energy demands such as transport, electricity and heat. In this paper an agent-based simulation model is developed to generate residential energy demand profiles in urban areas, influenced by factors such as land use, energy infrastructure and user behaviour. Within this framework, impact assessment of low carbon technologies such as plug-in electric vehicles and heat pumps is performed using London as a case study. The results show that the model can generate important insights as a decision support tool for the design and planning of sustainable urban energy systems.

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A Methodology for Simulating Synthetic Populations for the Analysis of Socio-technical Infrastructures

Cited by 8 publications

References 3 publications

A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

Modelling Individual Evacuation Decisions during Natural Disasters: A Case Study of Volcanic Crisis in Merapi, Indonesia

Simulating residential electricity and heat demand in urban areas using an agent-based modelling approach

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