CANS Lab，複雜適應性網絡與系統實驗室，長庚大學資訊工程學系

研究軟體與工具Research Software & Tools

CANS 實驗室 · 黃崇源教授CANS Lab · Prof. Chung-Yuan Huang

開源研究程式 Open-Source Research Software

以下為黃崇源教授及 CANS 實驗室團隊所開發的研究軟體與工具，所有程式碼皆以 MIT 授權公開於 GitHub，歡迎學術研究與教學使用。 The following research software and tools were developed by Prof. Chung-Yuan Huang and the CANS Lab team. All source code is released under the MIT License on GitHub for academic research and educational use.

  • EpiRank

    基於非對稱通勤網絡的疫情風險分析桌面應用程式。借鏡 Google PageRank 的哲學，EpiRank 同時模擬通勤的去程與回程方向，僅需單一通勤 OD 矩陣即可預測流感、腸病毒、SARS 三種疾病在臺灣 353 個鄉鎮的空間風險分布。 A desktop application for epidemic risk analysis across Taiwan's 353 townships based on asymmetric commuting networks. Inspired by Google's PageRank, EpiRank simultaneously models forward and return commuting trips to predict the spatial risk distribution of Influenza, Enterovirus, and SARS using a single commuting OD matrix.

    Epidemic Simulation PageRank Commuting Network Python GUI
    EpiRank sensitivity analysis heatmaps for damping factor and daytime parameter EpiRank vs actual disease core classification stacked bar charts Taiwan commuter flow network visualization and statistics EpiRank paper first page — Scientific Reports 2019
    論文：Paper: Huang, C.-Y., Chin, W. C. B., Wen, T.-H., Fu, Y.-H., & Tsai, Y.-S. (2019). EpiRank: Modeling Bidirectional Disease Spread in Asymmetric Commuting Networks. Scientific Reports, 9, 5415. doi:10.1038/s41598-019-41719-8
    GitHub Repository → · MIT License

  • HETA — Hierarchical Edge Type Analysis

    無參數的複雜網絡邊分類工具。HETA 純粹依據網絡拓撲結構，將每條邊分類為 BOND、SINK、LOCAL BRIDGE 或 GLOBAL BRIDGE 四種類型，無需預先定義社群標籤或邊權重。支援 PySide6 圖形介面與命令列雙模式。 A parameter-free tool for classifying every edge in a complex network into one of four structural types (BOND, SINK, LOCAL BRIDGE, GLOBAL BRIDGE) driven entirely by network topology, without requiring pre-defined community labels or edge weights. Offers both a PySide6 GUI and a full-featured CLI.

    Network Analysis Edge Classification Complex Networks Python GUI + CLI
    HETA edge type classification: Silk, Bond, Local Bridge, Global Bridge on example network HETA community detection on 4 real-world networks: rdgam, women, camp92, karate HETA link type analysis applied to 16 benchmark networks HETA paper first page — Physica A 2019
    論文：Paper: Huang, C.-Y., Chin, W. C. B., Fu, Y.-H., & Tsai, Y.-S. (2019). Beyond bond links in complex networks: Local bridges, global bridges and silk links. Physica A: Statistical Mechanics and its Applications, 536, 121027. doi:10.1016/j.physa.2019.04.263
    GitHub Repository → · MIT License

  • HATA — Hierarchical Arc Type Analysis

    有向網絡弧分類工具。HATA 將 HETA 框架擴展至有向圖，以方向性自我網絡取代「共同朋友」概念，將每條有向弧分類為 BOND、Silk、Local Bridge 或 Global Bridge。 A tool for classifying directed arcs in complex networks into four hierarchical types (BOND, Silk, Local Bridge, Global Bridge). HATA extends the HETA framework to directed networks by replacing the "common friends" concept with directional ego networks.

    Directed Networks Arc Classification Complex Networks Python
    HATA arc type classification: Silk, Bond, Local Bridge, Global Bridge on directed example network HATA arc classification on 4 directed networks: foodweb, citation, blogs, highschool HATA arc type proportions over time in Travian game networks HATA paper first page — IEEE Access 2020
    論文：Paper: Huang, C.-Y. & Chin, W. C. B. (2020). Distinguishing Arc Types to Understand Complex Network Strength Structures and Hierarchical Connectivity Patterns. IEEE Access, 8, 71021–71040. doi:10.1109/ACCESS.2020.2986017
    GitHub Repository → · MIT License

  • BCAT — Bounded Confidence and Adoption Threshold Model

    結合有界信心意見動態與採用門檻創新擴散的混合模擬模型，用於探索「最佳遊戲卻無人問津」現象。支援正規格子、小世界網絡、隨機網絡及無標度網絡四種拓撲。提供 Python 3 與 NetLogo 4.0.5 兩種實作。 A mixed opinion dynamics and innovation diffusion simulation model for exploring the "best game no one played" phenomenon. Supports Regular Lattice, Small-World, Random, and Scale-Free network topologies. Implementations available in Python 3 (with Tkinter GUI) and NetLogo 4.0.5.

    Opinion Dynamics Innovation Diffusion Agent-Based Model Python NetLogo
    BCAT correlation matrices across Regular Lattice, Small-World, Random, and Scale-Free networks BCAT simulation algorithm flowchart with opinion exchange and adoption decision phases BCAT GUI — opinion dynamics and adoption simulation with multiple charts BCAT paper first page — IEEE Access 2022
    論文：Paper: Wang, S.-W., Huang, C.-Y., & Sun, C.-T. (2022). Multiagent Diffusion and Opinion Dynamics Model Interaction Effects on Controversial Products. IEEE Access, 10, 115252–115270. doi:10.1109/ACCESS.2022.3218719
    GitHub Repository → · MIT License

  • SRAC-Agent

    演化空間囚徒困境賽局中自我聲譽感知機制的模擬器。研究代理人如何評估自身適應度與聲譽並據此調整策略。支援 50×50 格網上 2,500 個代理人的即時視覺化模擬，提供 GUI 與 CLI 雙模式及批次實驗功能。 A Python 3 simulator for studying the influence of self-reputation awareness on agent behavior in evolutionary spatial Iterated Prisoner's Dilemma (IPD) games. Simulates 2,500 agents on a 50×50 grid with real-time visualization, supporting both GUI and CLI modes with batch experiment capabilities.

    Game Theory Prisoner's Dilemma Evolutionary Computation Agent-Based Model Python
    SRAC-IPD initial random strategies on 50×50 cellular automata grid SRAC-IPD evolved strategies at generation 99 with SRAC agents enabled SRAC-Agent four key strategies dynamics — ALL-C, TFT, PAVLOV, ALL-D SRAC-Agent paper first page — PLOS ONE 2014
    論文：Paper: Huang, C.-Y. & Lee, C.-L. (2014). Influences of Agents with a Self-Reputation Awareness Component in an Evolutionary Spatial IPD Game. PLOS ONE, 9(6), e99841. doi:10.1371/journal.pone.0099841
    GitHub Repository → · MIT License

  • AED2 — AED Placement Optimization

    使用基因演算法最佳化自動體外心臟電擊去顫器（AED）的配置地點。基於臺北市 2010 年院外心跳停止（OHCA）案例資料，在超商網絡中找出最佳 AED 部署位置，以最大化 OHCA 存活率並提升成本效益。 A genetic algorithm for optimizing Automated External Defibrillator (AED) placement at convenience stores to maximize Out-of-Hospital Cardiac Arrest (OHCA) survival rates. Uses Taipei 2010 OHCA case data to identify optimal deployment locations with improved cost-effectiveness.

    Genetic Algorithm AED Placement Public Health Optimization
    Taipei City maps: (a) fire stations and OHCA cases, (b) current AED and 7-11 locations Density distribution comparison: (a) OHCA cases, (b) suggested AED placement locations AED2 optimization results: 49 stores in top 50 and 74 stores in top 10 across runs AED2 paper first page — Applied Geography 2012
    論文：Paper: Tsai, Y.-S., Ko, P. C.-I., Huang, C.-Y., & Wen, T.-H. (2012). Optimizing locations for the installation of automated external defibrillators (AEDs) in urban public streets through the use of spatial and temporal weighting schemes. Applied Geography, 35(1–2), 394–404. doi:10.1016/j.apgeog.2012.09.002
    GitHub Repository → · MIT License