Parallel Computing for Reconstructing Large-Scale Household Composition from Statistics for Agent-Based Social Simulations
Date:
論文情報
- 著者：Takuya HARADA，Tadahiko MURATA
- 会議名：Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
- 発表日：2017-06-29
- 記述言語：英語
- 発表形態：口頭発表
概要
In this paper, we employ parallel computing techniques to reconstruct large-scale household compositions for micro-simulations (MS) or agent-based simulations (ABS). For enabling MS or ABS, each household composition such as ages, occupations, or other properties of each member of a household should be prepared before simulations. However real household compositions are not available to researchers due to privacy or security reasons. In this paper, we propose a method to reconstruct a large-scale household composition based on statistics using parallel computing techniques. In order to generate artificial populations as soon as possible, parallel computing techniques are essential in reconstruction methods. In this paper, we show a challenge in an application of parallel computing to a previously proposed reconstruction method, and how to cope with that challenge.