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Construction of the evaluation system for earthquake forecasting models based on preseismic phenomena

Research Project

Project/Area Number 25750149
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Natural disaster / Disaster prevention science
Research InstitutionThe University of Tokyo

Principal Investigator

YOKOI Sayoko  東京大学, 地震研究所, 特任研究員 (70434842)

Research Collaborator OKADA Masami  
Project Period (FY) 2013-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords地震先行現象 / 検証方法
Outline of Final Research Achievements

We built a system to improve the accuracy of earthquake forecasting model based on observing the phenomena correlated with the earthquake and estimating the earthquake occurrence (preceding model). Specifically, the system provides a platform for prospective forecasting based on preceding models, and a fairly evaluations of the score of the preceding models. As a result of this, suspicion of the preceding model which had been publicly announced as a retrospective forecasting - the prediction was modified by the modeler of the preceding model after the earthquake occurred - was dispelled. Then, we became able to know the real forecasting abilities of the preceding models. The modelers can grasp the ability of their models by repeating the submission and evaluation of their predictions using this system. This system leads to improvement of models.

Report

(5 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • 2014 Research-status Report
  • 2013 Research-status Report

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Published: 2014-07-25   Modified: 2019-07-29  

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