Risk Evaluation by Human Trajectory Simulation Based on Real Data

2011 ◽  
Vol 15 (2) ◽  
pp. 220-225
Author(s):  
Kiyoshi Izumi ◽  
◽  
Yoshifumi Nishida ◽  
Yoichi Motomura ◽  
Keyword(s):  
Risk Evaluation ◽  
Real Data ◽  
Public Spaces ◽  
Layout Design ◽  
Sensor Data ◽  
Agent Based Simulation ◽  
New Approach ◽  
Agent Based ◽  
Trajectory Simulation ◽  
Simulation Based

This paper proposes a new approach integrating the modeling of moving persons from sensor data and agent-based simulation for indoor layout design viewed from preventing children’s accidents. Our model focuses on interaction between indoor objects and children to estimate the risk of indoor accidents. We discuss the agent-based simulation of multiple persons moving in public spaces and its application to evaluating information presentation for guidance.

Social and Group Simulation Based on Real Data Analysis

2011 ◽  
Vol 15 (2) ◽  
pp. 166-172
Author(s):  
Kiyoshi Izumi ◽  
◽  
Keiki Takadama ◽  
Hiromitsu Hattori ◽  
Nariaki Nishino ◽  
...  
Keyword(s):  
Data Analysis ◽  
Financial Marketing ◽  
Real Data ◽  
Social Simulation ◽  
Sustainable Society ◽  
Agent Based Simulation ◽  
Simulation Research ◽  
Agent Based ◽  
Simulation Based ◽  
General Method

Recently, social simulation research based on real data has appeared in various fields. This paper introduces studies of Agent-Based Simulation (ABSs) based on real data, focusing on introducing studies in the fields of financial marketing, traffic, pedestrians, and a sustainable society. We also introduce some approaches to establish a general method and/or theory about linking social simulation to real data. Finally, we categorize ABS research for understanding ABS research features.

scholarly journals Agent-Based Simulation of Hardware-Intensive Design Teams Using the Function–Behavior–Structure Framework

Systems ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 37 ◽  
Author(s):  
Mitch Bott ◽  
Bryan Mesmer
Keyword(s):  
Software Development ◽  
Case Studies ◽  
Design Teams ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Agile Processes ◽  
Structure Framework ◽  
Simulation Based ◽  
Space Launch ◽  
Intensive System

Agile processes have been used in software development, with many case studies indicating positive changes in productivity when these processes are used. Agile processes are beginning to be applied to work beyond software-centric systems. There does not yet exist a diverse set of studies on the effectiveness of Agile processes on hardware-intensive systems. The research in this article applies a modeling and simulation-based approach which uses the function–behavior–structure framework to evaluate the effectiveness of waterfall and Agile processes. The simulation was validated against case studies of software-centric design efforts. When applied to a space launch vehicle—a highly coupled, hardware-intensive system—the simulation shows that the benefits of Agile may not be as great as those seen with software-intensive systems.

scholarly journals Special Issue on New Trends in Agent-Based Simulation

2011 ◽  
Vol 15 (2) ◽  
pp. 165-165
Author(s):  
Keiki Takadama ◽  
Kiyoshi Izumi
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Computer Science ◽  
Mutual Influence ◽  
Real Data ◽  
Special Issue ◽  
Learning Mechanisms ◽  
Agent Based Simulation ◽  
Agent Based ◽  
The Social

Agent-Based Simulation (ABS), an interdisciplinary area embracing both the computer science and the social science, has attracted much attention and aided the understanding of socially complex phenomena. A current important issue in this research area is how to improve ABS effectiveness and comprehension, which makes further mutual influence between the computer science and the social sciences indispensable - e.g., (1) agent modeling involving learning mechanisms in the computer science and (2) social dynamics analysis needed in the social science. Such integration of these two areas would help fulfill the great potential of ABS, first in solving complex engineering problems using agent-based technology and second in developing and testing new theories on socially complex systems. This special issue features ABS papers from both of these important areas exploring new trends in ABS. The 10 papers composing this special issue start with papers by Nobutada Fujii and Hiroyasu Inoue analyzing the relationship between the network structure and system dynamics. In these papers, an agent-based computational economics approach has been active in applying agent-based technologies to financial and economic systems. Papers by Biliana Alexandrova-Kabadjova, Isamu Okada, TomokoOhi, and Nariaki Nishino cover consumer and financial markets using agent-based models. They test economic theory and examine market phenomena for market design. Agent-based simulation is increasingly used in application fields in the social sciences. Papers by Kiyoshi Izumi, Hideki Fujii, Hiromitsu Hattori, and Shigeo Sagai propose solutions for actual social problems such as injury prevention, traffic, and electrical power. Models are created based on behavior data, and the integration of an agent-based model and real data is a hot topic in this area. As the beginning of these technical papers, this issue starts by a position paper to give an ABS overview for understanding important issues in ABS from an overall viewpoint and for understanding state-of-the-art ABS. The information presented is invaluable in helping readers grasp the important features of ABS.

scholarly journals Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1626
Author(s):  
Svetozar Zarko Valtchev ◽  
Ali Asgary ◽  
Michael Chen ◽  
Felippe A. Cronemberger ◽  
Mahdi M. Najafabadi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Rapid Assessment ◽  
Real Data ◽  
Interdisciplinary Teams ◽  
Major Focus ◽  
Data Simulation ◽  
Agent Based ◽  
Simulation Based ◽  
New Methodologies ◽  
Testing Policies

Research on SARS-CoV-2 and its social implications have become a major focus to interdisciplinary teams worldwide. As interest in more direct solutions, such as mass testing and vaccination grows, several studies appear to be dedicated to the operationalization of those solutions, leveraging both traditional and new methodologies, and, increasingly, the combination of both. This research examines the challenges anticipated for preventative testing of SARS-CoV-2 in schools and proposes an artificial intelligence (AI)-powered agent-based model crafted specifically for school scenarios. This research shows that in the absence of real data, simulation-based data can be used to develop an artificial intelligence model for the application of rapid assessment of school testing policies.

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