Platform construction for hierarchical structure analysis of large scale spatio-temporal data and its application

2016 Fiscal Year Final Research Report

• Project/Area Number: 26330041
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Statistical science
• Research Institution: Okayama University
• Principal Investigator: Kurihara Koji 岡山大学, 環境生命科学研究科, 教授 (20170087)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 時空間情報 / エシェロン解析 / ホットスポット

Outline of Final Research Achievements

In this study, we have constructed a platform with a unified framework for hierarchical classification of in-phase and hotspot detection in a Markov random field where multivariate information is observed in spatiotemporal space. In addition, we established a new method on true integration and complexity for multivariate spatiotemporal information including large-scale information. We also created algorithms and software for hotspot detection and regional structure analysis in a unified framework for each field.

Free Research Field

総合領域