| Project/Area Number |
23540143
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
General mathematics (including Probability theory/Statistical mathematics)
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
KOMORI YOSHIO 九州工業大学, 大学院情報工学研究院, 准教授 (20285430)
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| Research Collaborator |
BURRAGE Kevin オックスフォード大学, コンピューティングラボラトリー, 教授
BUCKWAR Evelyn ヨハネスケプラー大学, 確率解析学研究所, 教授
TOCINO Angel サラマンカ大学, 数学科, 准教授
COHEN David ウメオ大学, 数学科, 講師
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| Project Period (FY) |
2011-04-28 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 数値解法 / 確率微分方程式 / 数値的安定性 / 数値シミュレーション / 生化学反応 / 陽的数値解法 / Exponential ルンゲ・クッタ法 / 国際研究者交流 / イギリス / 国際情報交流 / オーストリア |
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| Outline of Final Research Achievements |
We have derived new numerical methods for stochastic differential equations, which are ordinary differential equations with noise terms. For ordinary differential equations, there are well-known good methods, whose computational costs are relatively low and which can avoid numerical errors’ increasing. In the present study, we have succeeded in developing them into ones for stochastic differential equations, while keeping their advantages. As a practical example, we have applied our methods for simulation of biochemical reaction system, and showed the good performance of them.
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