scholarly journals Simulation Models on Human--Nature Interactions in Urban Landscapes: A Review Including Spatial Economics, System Dynamics, Cellular Automata and Agent-based Approaches

2009 ◽  
Vol 3 ◽  
Author(s):  
Dagmar Haase ◽  
Nina Schwarz
Keyword(s):  
Cellular Automata ◽  
System Dynamics ◽  
Human Nature ◽  
Simulation Models ◽  
Spatial Economics ◽  
Urban Landscapes ◽  
Agent Based

Simulation modeling of the smart city system: The concept, methods, and cases

2020 ◽  
Vol 19 (2) ◽  
pp. 226-250 ◽  
Author(s):  
V.L. Makarov ◽  
R.A. Bakhtizin ◽  
G.L. Beklaryan ◽  
A.S. Akopov
Keyword(s):  
Decision Making ◽  
Urban Planning ◽  
System Dynamics ◽  
Smart City ◽  
Simulation Modeling ◽  
Simulation Models ◽  
Agent Based Modeling ◽  
Decision Making Process ◽  
Agent Based ◽  
City System

Subject. The research investigates key processes of urban life and its maintenance, including food supply, infrastructure, fire security, quality and accessibility of medical services, etc. The article also discusses the creation of a system supporting the Smart City decision-making process. Objectives. The research develops methods and tools to manage the Smart City system through system dynamics and agent-based modeling. Methods. Using simulation modeling, namely system dynamics and agent-based modeling (supported via Powersim and AnyLogic), we evaluate how multiple guiding parameters influence crucial characteristics of the Smart City system. Results. We devised an approach to designing the Smart City system through methods of system dynamics and agent-based modeling (supported via Powersim and AnyLogic) intended to streamline the decision making process for reasonable urban planning. Conclusions and Relevance. We propose the consolidated architecture of the Smart City decision-making system integrating the simulation models, data storage and city monitoring subsystem. The article describes the cases of simulation models implemented via Powersim and AnyLogic to support rational urban planning. The simulation models will significantly improve the quality of urban environment, satisfy the demand for food products, provide access to healthcare services and ensure effective rescue actions in case of emergency.

A modeling framework for the application of multi-paradigm simulation methods

SIMULATION ◽  
2019 ◽  
Vol 96 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Konstantinos Mykoniatis ◽  
Anastasia Angelopoulou
Keyword(s):  
System Dynamics ◽  
Modeling And Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Discrete Event System ◽  
Modeling Framework ◽  
Agent Based ◽  
Event System ◽  
Generic Modeling ◽  
Generic Relationships

Decisions about modeling and simulation (M&S) of real-world systems need to be evaluated prior to implementation. Discrete Event, System Dynamics, and Agent Based are three different modeling and simulation approaches widely applied to enhance decision-making of M&S of these systems. Combining and/or integrating these methods can provide solutions to a plethora of systems’ problems. However, current solutions and frameworks do not provide guidance for selecting and deploying M&S models. Hence, the aim of this work is to present a generic modeling framework for combining and/or integrating Discrete Event, System Dynamics, and Agent Based simulation approaches. The framework is termed multi-paradigm modeling framework (MPMF). In this paper, we describe the research methodology that was followed for the development of MPMF, the different phases of MPMF, and the generic relationships of forming and deploying multi-paradigm simulation models. Then we evaluate the framework by using it for the implementation of a universal task analysis simulation model (UTASiMo). The MPMF provided guidance on what methods need to be incorporated into the UTASiMo models, what information is exchanged among those models, and how these models are connected and interact with each other.

scholarly journals A Literature Review of Hybrid System Dynamics and Agent-Based Modeling in a Produced Water Management Context

Modelling ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 224-239
Author(s):  
Saeed P. Langarudi ◽  
Robert P. Sabie ◽  
Babak Bahaddin ◽  
Alexander G. Fernald
Keyword(s):  
Water Management ◽  
New Mexico ◽  
Literature Review ◽  
System Dynamics ◽  
Oil And Gas ◽  
Produced Water ◽  
Hybrid Approach ◽  
Oil And Gas Industry ◽  
Hybrid Modeling ◽  
Agent Based

This paper explores the possibility and plausibility of developing a hybrid simulation method combining agent-based (AB) and system dynamics (SD) modeling to address the case study of produced water management (PWM). In southeastern New Mexico, the oil and gas industry generates large volumes of produced water, while at the same time, freshwater resources are scarce. Single-method models are unable to capture the dynamic impacts of PWM on the water budget at both the local and regional levels, hence the need for a more complex hybrid approach. We used the literature, information characterizing produced water in New Mexico, and our preliminary interviews with subject matter experts to develop this framework. We then conducted a systematic literature review to summarize state-of-the-art of hybrid modeling methodologies and techniques. Our research revealed that there is a small but growing volume of hybrid modeling research that could provide some foundational support for modelers interested in hybrid modeling approaches for complex natural resource management issues. We categorized these efforts into four classes based on their approaches to hybrid modeling. It appears that, among these classes, PWM requires the most sophisticated approach, indicating that PWM modelers will need to face serious challenges and break new ground in this realm.

Agents in bioinformatics

2005 ◽  
Vol 20 (2) ◽  
pp. 117-125 ◽  
Author(s):  
MICHAEL LUCK ◽  
EMANUELA MERELLI
Keyword(s):  
Data Analysis ◽  
Simulation Models ◽  
Biological Data ◽  
System Modelling ◽  
Agent Based Simulation ◽  
Huge Amount ◽  
Agent Based ◽  
Information Agents ◽  
New Knowledge ◽  
Definition Of

The scope of the Technical Forum Group (TFG) on Agents in Bioinformatics (BIOAGENTS) was to inspire collaboration between the agent and bioinformatics communities with the aim of creating an opportunity to propose a different (agent-based) approach to the development of computational frameworks both for data analysis in bioinformatics and for system modelling in computational biology. During the day, the participants examined the future of research on agents in bioinformatics primarily through 12 invited talks selected to cover the most relevant topics. From the discussions, it became clear that there are many perspectives to the field, ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages for use by information agents, and to the use of Grid agents, each of which requires further exploration. The interactions between participants encouraged the development of applications that describe a way of creating agent-based simulation models of biological systems, starting from an hypothesis and inferring new knowledge (or relations) by mining and analysing the huge amount of public biological data. In this report we summarize and reflect on the presentations and discussions.

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