Generalize scaling method for mathematical and informational understandings of Complex systems
| Project/Area Number |
17500138
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Chiba University |
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Principal Investigator |
MATSUBA Ikuo Chiba University, Graduate School of Advanced Integration Science, Professor (30251177)
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| Co-Investigator(Kenkyū-buntansha) |
KAWARADA Hideo Ruytsu Keizai University, Distribution and logistics, Professor (90010793)
KOSHIGOE Hideyuki Chiba University, Graduate School of Engineering, Associate Professor (70110294)
MORI Yasukuni Chiba University, Graduate School of Advanced Integration Science, Assistant Professor (40361414)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥240,000)
Fiscal Year 2007: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2006: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2005: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | Soft computing / Self organization / Mathematical engineering |
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| Research Abstract |
It is a common feature of some physical systems consisting of a large number of coupled systems that a cascade of energy flow from large to small scales generates a scaling behavior, namely power-law behavior of some observable. Scaling is found in a wide range of systems, from geophysical to biological. A typical example is seismicity that is characterized by an energy transfer through a hierarchy structure. One of recent research is to apply this idea to explain the observed scaling laws. In this study, we proposed the general framework of scaling with many variables and its method that exhibit self-similar properties. The commonly used dynamically driven fractal method is useful to analyze the scale invariance of the spatiotemporal structures produced by the operation of the updating algorithm. This method integrates the model in space and time in the analysis of the effect of coarse graining on the dynamics to produce the set of scaling equations from which various characteristic exponents are obtained.
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Report
(4 results)
Research Products
(34 results)
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[Book] 長期記憶過程の統計2007
Author(s)
松葉育雄
Total Pages
359
Publisher
共立出版
Description
「研究成果報告書概要(和文)」より
Related Report
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[Book] 人工知能学辞典2005
Author(s)
松葉育雄(人工知能学会編集)
Total Pages
976
Publisher
共立出版
Description
「研究成果報告書概要(和文)」より
Related Report
