| 研究実績の概要 |
In the 2017 fiscal year, the research progress of this project is very good, and our research achievements can be summarized as follows:
(1)Firstly, we successfully collected big and heterogeneous data sources for the entire research. To manage these data, we developed a Hadoop cluster that consists of 32 cores, 32 GB memory, and 16 TB storage, and is able to run 28 tasks simultaneously.(2)Secondly, we build an online system called DeepUrban-Momentum to conduct the next short-term mobility predictions by using (the limited steps of) currently observed human mobility data. We apply our system to a real emergency scenario and demonstrate that our system is applicable in the real world.
Our research results were published in the eminent publications for computer science including AAAI 2018.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
In the 2017 fiscal year, the research progress of this project is very good. Firstly, we successfully collected big and heterogeneous data sources for the entire research.Secondly, we build an online system called DeepUrban-Momentum to conduct the next short-term mobility predictions by using (the limited steps of) currently observed human mobility data. We apply our system to a real emergency scenario and demonstrate that our system is applicable in the real world.
Our research results were published in the eminent publications for computer science including AAAI 2018.
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| 今後の研究の推進方策 |
In the 2018 fiscal year, we will focus on developing novel approaches and deep models to predict human disaster behavior, mobility and preference. Meanwhile, we will also focus on the evaluation of the developed algorithms.
We will (1) use standard performance metrics used in the research literature and carefully compare our algorithms with existing work when applicable; (2) explore the trade-offs between competing alternative parameter settings through the design of suitable experiments; and (3) work closely with domain experts to evaluate and validate the results.
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