scholarly journals ANALYSIS OF THE ROAD NETWORK STRUCTURES BASED ON STREET CONNECTIVITY

Contexto ◽  
2020 ◽  
Vol 14 (20) ◽  
Author(s):  
María Erándi Flores Romero ◽  
Irving Omar Morales Agiss ◽  
Liliana Beatriz Sosa Compean
Keyword(s):  
Community Detection ◽  
Road Network ◽  
Public Policies ◽  
Detection Algorithm ◽  
Street Connectivity ◽  
Urban Mobility ◽  
Road Infrastructure ◽  
The Road ◽  
Community Detection Algorithm ◽  
The City

The following article proposes a method to identify structures inside a road network with a flow-base community detection algorithm implemented on a graph representing the city road network. According to the results obtained in the cities of Mexico and Monterrey, the method effectively divides road infrastructure into several communities and preserves geographical neighboring. The frontiers of communities match administrative divisions along with other frontiers inside the city. The identification of communities could be useful to study the heterogeneity of street connectivity inside the city which could lead to improvements in urban mobility or even the application of public policies.

scholarly journals Saving Travel Time as an Urban Planning Instrument. Case Study: Manizales, Colombia

2018 ◽  
Vol 12 (6) ◽  
pp. 44 ◽  
Author(s):  
Carlos Alberto Moncada ◽  
Santiago Cardona ◽  
Diego Alexander Escobar
Keyword(s):  
Travel Time ◽  
Direct Influence ◽  
Urban Mobility ◽  
Road Infrastructure ◽  
Urban Road ◽  
The Road ◽  
Average Travel Time ◽  
Future Situation ◽  
The City

This research explores the benefits of a proposal for urban road infrastructure which aims to improve road connection between northwest and western neighborhoods of the city of Manizales, Colombia, as well as to expand the ring of urban mobility that runs through the city. By calculating the global average accessibility and comparing the current and future situation, by averages of savings gradient, timesaving generated by this alternative are obtained in terms of average travel time. There is evidenced that suggest the road infrastructure proposal would generate savings in the average travel times for the entire city, especially to the neighborhoods located in the area of direct influence.

scholarly journals Overlapping Community Detection Based on Attribute Augmented Graph

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 680
Author(s):  
Hanyang Lin ◽  
Yongzhao Zhan ◽  
Zizheng Zhao ◽  
Yuzhong Chen ◽  
Chen Dong
Keyword(s):  
Community Detection ◽  
Real World ◽  
Detection Algorithm ◽  
Overlapping Community Detection ◽  
Overlapping Communities ◽  
Adjustment Strategy ◽  
Topology Information ◽  
Overlapping Community ◽  
Real World Datasets ◽  
Community Detection Algorithm

There is a wealth of information in real-world social networks. In addition to the topology information, the vertices or edges of a social network often have attributes, with many of the overlapping vertices belonging to several communities simultaneously. It is challenging to fully utilize the additional attribute information to detect overlapping communities. In this paper, we first propose an overlapping community detection algorithm based on an augmented attribute graph. An improved weight adjustment strategy for attributes is embedded in the algorithm to help detect overlapping communities more accurately. Second, we enhance the algorithm to automatically determine the number of communities by a node-density-based fuzzy k-medoids process. Extensive experiments on both synthetic and real-world datasets demonstrate that the proposed algorithms can effectively detect overlapping communities with fewer parameters compared to the baseline methods.

scholarly journals City consumption profile: a city perspective on the spending behavior of citizens

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Alessia Galdeman ◽  
Cheick T. Ba ◽  
Matteo Zignani ◽  
Christian Quadri ◽  
Sabrina Gaito
Keyword(s):  
Credit Card ◽  
Detection Algorithm ◽  
Economic Behavior ◽  
Single Type ◽  
Goods And Services ◽  
Usage Patterns ◽  
Spending Behavior ◽  
Community Detection Algorithm ◽  
The City ◽  
Consumption Profile

AbstractIn designing the city of the future, city managers and urban planners are driven by specific citizens’ behaviors. In fact, economic and financial behaviors, and specifically, which goods and services citizens purchase and how they allocate their spending, are playing a central role in planning targeted services. In this context, cashless payments provide an invaluable data source to identify such spending behaviors. In this work, we propose a methodology to extract the consumption behaviors of a large sample of customers through credit card transaction data. The main outcome of the methodology is a concise representation of the economic behavior of people residing in a city, the so-called city consumption profile. We inferred the city consumption profile from a network-based representation of the similarity among the customers in terms of purchase allocation; on top of which we applied a community detection algorithm to identify the representative consumption profiles. By applying the above methodology to a set of credit card transactions of an Italian financial group, we showed that cities, even geographically close, exhibit different profiles which makes them unique. Specifically, usage patterns focused on a single type of good/service—mono-categorical consumption profile—are the main factors leading to the differences in the city profiles. Our analysis also showed that there is a group of consumption profiles common to all cities, made up by purchases of primary goods/services, such as food or clothing. In general, the city consumption profile represents a tool for understanding the economic behaviors of the citizens and for comparing different cities. Moreover, city planners and managers may use it in the outline of city services tailored to the citizens’ needs.

Sign in / Sign up

Export Citation Format

Share Document