Development of Efficient Methods for Optimizing the Structure of Networked Systems Based on Various Measures
| Project/Area Number |
15K00035
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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 |
Mathematical informatics
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| Research Institution | Okayama University |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | ネットワーク / 構造最適化 / 代数的連結度 / クラスタ係数 / 媒介中心性 / 平均頂点間距離 / コミュニティ検出 / 非負値行列因子分解 / 平均最短経路長 / 一般化de Bruijnグラフ / 一般化Mooreグラフ / マルチエージェントネットワーク / 複雑ネットワーク / コミュニティー検出 / ストリームアルゴリズム / 分散アルゴリズム |
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| Outline of Final Research Achievements |
We studied the problem of optimizing the network topology based on various measures such as the algebraic connectivity, the clustering coefficient, the betweenness centrality, the average shortest path length, and so on. We not only derived the algebraic connectivity maximizing (or locally maximizing) graphs, the clustering coefficient locally maximizing graphs, and the global clustering coefficient maximizing graphs through theoretical analysis, but also developed various algorithms for optimizing the network topology based on the betweenness centrality and the average shortest path length. We also developed some decentralized algorithms for computing the algebraic connectivity, and some fast methods for nonnegative matrix factorization to solve the problem of community detection.
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Report
(4 results)
Research Products
(44 results)
