| Project/Area Number |
24650116
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Tokyo University of Science (2014-2015)
Saitama University (2012-2013) |
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Principal Investigator |
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| Project Period (FY) |
2012-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2012: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 複雑ネットワーク / 時間発展 / 時系列 / 予測 / 状態同定 / テンポラルネットワーク / 古典的多次元尺度法 / カオス / 非線形時系列解析 / 非線形予測 / 情報伝播 |
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| Outline of Final Research Achievements |
We propose a new framework to analyze characteristics of temporal networks and to predict how the temporal networks evolve. Using the theory and techniques of nonlinear time series analysis, we first show that the proposed method in the framework can effectively transform complex networks to time series. The results show that we can analyze the temporal evolution of complex networks by the time series analysis theory. In addition, we also analyze real temporal network data (sending and receiving records of electronic mails in a private company) and model its statistical behavior. Analyzing the real data of the temporal networks, we discovered that the records have several interesting temporal features. Then, we propose m The results show that our model can reproduce several characteristics of the real network data.
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