International Conference on Computer and Knowledge Engineering

Home / 11th International Conference on Computer and Knowledge Engineering

Investigation of topological characteristics of Iranian railway network: A network science approach

Authors :

Sina Firuzbakht¹ Mohammad Khansari²

1- University of Tehran 2- University of Tehran

Keywords :

network analysis, railway network, complex network, network science, small world phenomenon, vulnerability

Abstract :

In this paper, we study the Iranian railway network as a complex network so that train stations form network nodes and a direct route between two stations of network edges. With the help of investigating the topological characteristics of the network, such as betweenness centrality, we found vulnerable stations and routes. Then, by finding the degree distribution, diameter, and average path length of the railway network, we have examined the existence or non-existence of the small world phenomenon in the network After realizing that there is no small world phenomenon in Iran's railway network, we concluded that the gradual development of Iran's railway network not based on economic optimization and economic or political or regional factors played a more important role in its development.

List of archived papers

Exploring 3D Transfer Learning CNN Models for Alzheimer’s Disease Diagnosis from MRI Images

Fatemehsadat Ghanadi Ladani - Hamidreza Baradaran Kashani

Automatic Generation of XACML Code using Model-Driven Approach

Athareh Fatemian - Bahman Zamani - Marzieh Masoumi - Mehran Kamranpour - Behrouz Tork Ladani - Shekoufeh Kolahdouz Rahimi

Graph Representation Learning Towards Patents Network Analysis

Mohammad Heydari - Babak Teimourpour

Systematic review on AI techniques in detection and navigation of agricultural machines and robots

Afsaneh Soleimani - Mohammad Boghrati - Hossein Damavandi

A parallel CNN-BiGRU network for short-term load forecasting in demand-side management

Arghavan Irankhah - Sahar Rezazadeh Saatlou - Mohammad Hossein Yaghmaee - Sara Ershadi-Nasab - Mohammad Alishahi

Enhanced Melanoma Detection: An Improved Deformable DETR Model with Efficient Channel Attention

Amirreza Rouhbakhshmeghrazi - Shayan Nalbandian - Sheida Shadman - Mohammad Reza Hassannezhad - Shuyuan Yang - Bo Li

Hardware-Efficient Pruned CNN Optimized by Neural Architecture Search and Genetic Algorithm for Diabetic Retinopathy Detection on STM32F746

Omid Askari Haddad - Sara Ershadi-Nasab

Evaluating the Impact of Traveling on COVID-19 Prevalence and Predicting the New Confirmed Cases According to the Travel Rate Using Machine Learning: A Case Study in Iran

Anita Ghandehari - Soheil Shirvani - Hadi Moradi

A 2D-CNN Architecture for Improving the Classification Accuracy of an Electronic Nose with Different Sensor Positions

Hannaneh Mahdavi - Reza Goldoust - Saeideh Rahbarpour

Real-Time Gender Recognition with a Deep Neural Network

Samad Azimi Abriz - Majid Meghdadi

more

Samin Hamayesh - Version 42.7.0