A New k-Graph Partition Algorithm for Distributed P2P Simulation Systems

2007 ◽  
pp. 391-402
Author(s):  
Chunjiang Wu ◽  
Shijie Zhou ◽  
Linna Wei ◽  
Jiaqing Luo ◽  
Yanli Wang ◽  
...  
Keyword(s):  
Graph Partition ◽  
Simulation Systems

An Interactive Graph Partition Method Through Combination of Multi-scale Analysis and Level Set

2013 ◽  
Vol 34 (9) ◽  
pp. 2078-2084 ◽  
Author(s):  
Yun-fei Wang ◽  
Du-yan Bi ◽  
De-qin Shi ◽  
Tian-jun Huang ◽  
Di Liu
Keyword(s):  
Level Set ◽  
Graph Partition ◽  
Scale Analysis ◽  
Multi Scale ◽  
Partition Method ◽  
Multi Scale Analysis

Design and analysis of auxiliary power supply simulation systems using the NEDIS language facilities

Cybernetics ◽  
1989 ◽  
Vol 24 (3) ◽  
pp. 315-319
Author(s):  
A. S. Zhernenko ◽  
O. A. Kokov ◽  
S. A. Trufanova ◽  
I. Z. Yakhimovich
Keyword(s):  
Power Supply ◽  
Auxiliary Power ◽  
Simulation Systems

Auto City: A System for Generating 3D Virtual Cities for Simulation Systems on GIS Maps

2009 ◽  
Vol 15 (1) ◽  
pp. 29-39 ◽  
Author(s):  
H. Haldun Göktaş ◽  
Abdullah Çavuşoğlu ◽  
Baha şen
Keyword(s):  
Simulation Systems

Statewide Simulation Systems: The Next Step for Anesthesiology?

2007 ◽  
Vol 25 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Michael Seropian ◽  
Dawn Dillman ◽  
David Farris
Keyword(s):  
Simulation Systems

scholarly journals A new multi-level algorithm for balanced partition problem on large scale directed graphs

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Xianyue Li ◽  
Yufei Pang ◽  
Chenxia Zhao ◽  
Yang Liu ◽  
Qingzhen Dong
Keyword(s):  
Large Scale ◽  
Directed Graphs ◽  
Vlsi Design ◽  
Graph Partition ◽  
Partition Problem ◽  
Multi Level ◽  
The Stability ◽  
Recursive Partition ◽  
Balanced Partition ◽  
Partition Method

AbstractGraph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new instance of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

scholarly journals Collision avoidance during group evasive manoeuvres: a comparison of real versus simulated swarms with manipulated vision and surface wave detectors

2014 ◽  
Vol 281 (1788) ◽  
pp. 20140812 ◽  
Author(s):  
William L. Romey ◽  
Magenta M. Miller ◽  
Jose M. Vidal
Keyword(s):  
Surface Wave ◽  
Sensory Modality ◽  
Simulation Models ◽  
Emergent Properties ◽  
Control Groups ◽  
Group Attraction ◽  
Group Motion ◽  
Coordinate Group ◽  
Group Movements ◽  
Simulation Systems

Coordinated group motion has been studied extensively both in real systems (flocks, swarms and schools) and in simulations (self-propelled particle (SPP) models using attraction and repulsion rules). Rarely are attraction and repulsion rules manipulated, and the resulting emergent behaviours of real and simulation systems are compared. We compare swarms of sensory-deprived whirligig beetles with matching simulation models. Whirligigs live at the water's surface and coordinate their grouping using their eyes and antennae. We filmed groups of beetles in which antennae or eyes had been unilaterally obstructed and measured individual and group behaviours. We then developed and compared eight SPP simulation models. Eye-less beetles formed larger diameter resting groups than antenna-less or control groups. Antenna-less groups collided more often with each other during evasive group movements than did eye-less or control groups. Simulations of antenna-less individuals produced no difference from a control (or a slight decrease) in group diameter. Simulations of eye-less individuals produced an increase in group diameter. Our study is important in (i) differentiating between group attraction and repulsion rules, (ii) directly comparing emergent properties of real and simulated groups, and (iii) exploring a new sensory modality (surface wave detection) to coordinate group movement.

Research on Spectral Clustering

2014 ◽  
Vol 687-691 ◽  
pp. 1350-1353
Author(s):  
Li Li Fu ◽  
Yong Li Liu ◽  
Li Jing Hao
Keyword(s):  
Spectral Clustering ◽  
Clustering Algorithm ◽  
Theoretical Foundation ◽  
Clustering Algorithms ◽  
Spectral Graph Theory ◽  
Graph Partition ◽  
Mining Areas ◽  
Spectral Graph ◽  
Definition Of ◽  
Spectral Clustering Algorithm

Spectral clustering algorithm is a kind of clustering algorithm based on spectral graph theory. As spectral clustering has deep theoretical foundation as well as the advantage in dealing with non-convex distribution, it has received much attention in machine learning and data mining areas. The algorithm is easy to implement, and outperforms traditional clustering algorithms such as K-means algorithm. This paper aims to give some intuitions on spectral clustering. We describe different graph partition criteria, the definition of spectral clustering, and clustering steps, etc. Finally, in order to solve the disadvantage of spectral clustering, some improvements are introduced briefly.

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