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Network Analysis Course

building level accessibility to services analysis using OSM road network

Syllabus

http://www4.huji.ac.il/htph/shnaton/index.php/NewSyl/40892/2/2019/

Network analysis - 40892 Last update 24-02-2019

HU Credits: 2

Degree/Cycle: 2nd degree (Master)

Responsible Department: Geography

Academic year: 0

Semester: 2nd Semester

Teaching Languages: Hebrew

Campus: Mt. Scopus

Course/Module Coordinator: Dr. Michal Lichter

Coordinator Email: [email protected]

Coordinator Office Hours:

Teaching Staff: Dr. Michal Lichter

Course/Module description: The course will review selected topics in network analysis with an emphasis on spatial applications in a GIS (Geographic Information System). In the course, students will learn to analyze real world data and use NetworkX and other python libraries.

Course/Module aims: Acquiring knowledge and skills to analyse networks

Learning outcomes - On successful completion of this module, students should be able to:

  • Describe what are networks and explain basic network theory concepts
  • Represent networks in different ways and describe the benefits and drawbacks of each
  • Analyse network using different python libraries
  • Characterise networks using various measures
  • Apply and perform various analyses on different types of networks *Attendance requirements(%): 80

Teaching arrangement and method of instruction:

Course/Module Content:

presentations: https://drive.google.com/drive/folders/1YfkPq4rDZryyUJcRhitU2t31aBSy5xH1?usp=sharing

  • Introduction
    • General concepts
  • Network types
  • Paths
    • Depth First Search (DFS)
    • Breadth First Search (BFS)
    • Shortest path problem
    • Dijkstra
  • Network Properties
    • Distance measures
    • Clustering Coefficient
    • Connected Components
  • Social Networks and centrality and influence measures
  • Road and transportation networks and accessibility and connectivity measures
  • Route problems
    • Seven bridges of Königsberg
    • Traveling salesman problem

Required Reading:

List of tutorials:

Python resources:

General python: https://interactivepython.org/courselib/static/thinkcspy/index.html

Additional Reading Material:

Course/Module evaluation:

  • End of year written/oral examination 0 %
  • Presentation 0 %
  • Participation in Tutorials 0 %
  • Project work 0 %
  • Assignments 100 %
  • Reports 0 %
  • Research project 0 %
  • Quizzes 0 %
  • Other 0 %