324,664 research outputs found
Community detection and graph partitioning
Many methods have been proposed for community detection in networks. Some of
the most promising are methods based on statistical inference, which rest on
solid mathematical foundations and return excellent results in practice. In
this paper we show that two of the most widely used inference methods can be
mapped directly onto versions of the standard minimum-cut graph partitioning
problem, which allows us to apply any of the many well-understood partitioning
algorithms to the solution of community detection problems. We illustrate the
approach by adapting the Laplacian spectral partitioning method to perform
community inference, testing the resulting algorithm on a range of examples,
including computer-generated and real-world networks. Both the quality of the
results and the running time rival the best previous methods.Comment: 5 pages, 2 figure
Frequency and voltage partitioning in presence of renewable energy resources for power system (example: North Chile power network)
This paper investigates techniques for frequency and voltage partitioning of power network based on the
graph-theory. These methods divide the power system into distinguished regions to avoid the spread of disturbances
and to minimize the interaction between these regions for frequency and voltage control of power system. In case
of required active and reactive power for improving the performance of the power system, control can be performed
regionally instead of a centralized controller. In this paper, renewable energy sources are connected to the power
network to verify the effect of these sources on the power systems partitioning and performance. The number of
regions is found based on the frequency sensitivity for frequency partitioning and bus voltage for voltage partitioning to disturbances being applied to loads in each region. The methodology is applied to the north part of Chile power
network. The results show the performance and ability of graph frequency and voltage partitioning algorithm to divide
large scale power systems to smaller regions for applying decentralized controllers.Peer ReviewedPostprint (published version
Distinguishing niche and neutral processes: issues in variation partitioning statistical methods and further perspectives
Variance partitioning methods, which are built upon multivariate statistics,
have been widely applied in different taxa and habitats in community ecology.
Here, I performed a literature review on the development and application of the
methods, and then discussed the limitation of available methods and the
difficulties involved in sampling schemes. The central goal of the work is then
to propose some potential practical methods that might help to overcome
different issues of traditional least-square-based regression modeling. A
variety of regression models has been considered for comparison. In initial
simulations, I identified that generalized additive model (GAM) has the highest
accuracy to predict variation components. Therefore, I argued that other
advanced regression techniques, including the GAM and related models, could be
utilized in variation partitioning for better quantifying the aggregation
scenarios of species distribution.Comment: 19 pages; 4 figure
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