At the end of the execution, the maximum value of modularity obtained will be returned, and the classification of nodes in groups in some output file (in the Pajek format, the output file is of type ...

Modularity is widely used in community detection in network. Despite its great success, one drawback is that its optimization is an NP-complete problem. To this end, this paper designs a new ...

Learn about some common graph algorithms for network analysis and optimization, such as shortest path, maximum flow, minimum spanning tree, centrality, and community detection. Agree & Join LinkedIn ...

One issue that has received a considerable amount of attention is the detection and characterization of community structure in networks (7, 8), meaning the appearance of densely connected groups of ...

For weighted graphs and globally thresholded binary graphs, modularity was also lower in COS, but for a narrower range of costs (Figures 3 and 6A,B). Similar results were found with the unsupervised ...

Now I am wondering how, assumed I interpreted the output correctly, I can find out more about the resistance of the continuous surface. After I did a single surface optimization for the continous ...

Dynamic (temporal) graphs are a convenient mathematical abstraction for many practical complex systems including social contacts, business transactions, and computer communications. Community ...

The Louvain algorithm results were derived from the median modularity value. Similarly, the SA algorithm was run with a high initial temperature and gradual cooling, with 1000 iterations per ...

The graph below shows the total number of publications each year in Process Flexibility and Design Optimization. References [1] Process flexibility in the presence of product modularity: Does ...