網路科學與架構
Network Science, Models, and Architecture
| 節 | 週二 |
|---|---|
7 15:30–16:20 | 網路科學與架構 ED102 3 節連堂 |
8 16:30–17:20 | |
9 17:30–18:20 |
* 根據陽明交大上課時間表所列
課程概述與目標: The course provides a comprehensive exploration of the interdisciplinary field of network science, focusing on the study of complex networks, their representation, modeling, and architectural implications. This course aims to equip students with a deep understanding of network science theories, models, and practical applications in diverse domains. By combining mathematical and computational approaches, students will develop the necessary skills to analyze, design, and optimize networks in real-world settings. 本課程全面探索跨學科領域的網路科學,專注於複雜網路的研究,包括其表示、模型化及架構上的影響。此課程旨在使學生深入瞭解網路科學的理論、模型和在不同領域的實際應用。透過數學和計算方法的結合,學生將發展必要的技能,以分析、設計和優化現實世界中的網路。
作業: 40% 期中考: 30% 期末考: 30%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to Network Science: (1) Overview of network science (2) Empirical study of real-world networks 網路科學入門: (1) 網路科學概述 (2) 對現實世界網路的實證研究 |
| 第 2 週 | Mathematics of Networks: (1) Networks and their representation (2) Basics of graph theory and network representation 網路的數學基礎: (1) 網路及其表示 (2) 圖論和網路表示的基礎 |
| 第 3 週 | Mathematics of Networks: (1) Extended features and characteristics of networks (2) Basics of graph representation learning 網路的數學基礎: (1) 網路的擴展特性和特徵 (2) 圖形表示學習的基礎知識 |
| 第 4 週 | Random Graph Models: (1) Introduction to random graph models (2) Properties and characteristics of the Erdos-Renyi model 隨機圖模型: (1) 隨機圖模型介紹 (2) Erdos-Renyi 模型的性質和特徵 |
| 第 5 週 | (Public Holiday) |
| 第 6 週 | Small-World Networks: (1) Introduction to small-world models (2) Properties and characteristics 小世界網路: (1) 小世界現象及小世界網路介紹 (2) 模型的特性 (+Scale-Free Networks) |
| 第 7 週 | Scale-Free Networks: (1) Introduction to scale-free networks (2) Properties and characteristics of the Price and Barabasi-Albert models (3) Preferential attachment and growth mechanisms 無尺度網路: (1) 無尺度網路介紹 (2) Price 和 Barabasi-Albert 模型的特性和特點 (3) 偏好連結和成長機制 |
| 第 8 週 | Midterm Test |
| 第 9 週 | Community structure: (1) Introduction to community structure and community detection (2) Community detection methods |
| 第 10 週 | Robustness and Resilience: (1) Percolation theory (2) Cascading failures (3) Robustness enhancement |
| 第 11 週 | Robustness and Resilience: (1) Percolation theory (2) Cascading failures (3) Robustness enhancement |
| 第 12 週 | Spreading Phenomenon: (1) Epidemic modeling & network epidemics (2) Contact networks (3) Epidemic prediction & prevention |
| 第 13 週 | Spreading Phenomenon: (1) Epidemic modeling & network epidemics (2) Contact networks (3) Epidemic prediction & prevention |
| 第 14 週 | Graph Isomorphism Problem |
| 第 15 週 | Graph Isomorphism Problem |
| 第 16 週 |
書名: Networks (Second Edition); 作者: Mark Newman; 出版社: Oxford University Press; 出版年: 2018. 書名: Network Science; 作者: A-L Barabasi; 出版年: 2016. Online available: http://networksciencebook.com/
- 時間
- TBD
- 聯絡方式
- Email: felix.lou@ieee.org (樓洋老師)