DocumentCode
3101955
Title
Single phase algorithm for hierarchical graph visualization
Author
Kusnadi ; Carothers, Jo Dale ; Chow, Felix ; Beebe, Craig
Author_Institution
Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
Volume
3
fYear
1995
fDate
22-25 Oct 1995
Firstpage
2025
Abstract
Presents an algorithm to visualize hierarchical graphs which allows simultaneous minimization of the crossing number and total path length. The algorithm is based on a Hopfield-type neural network: employing the binary decision neuron model. The authors also compare the output results with those of heuristic methods. In terms of the readability requirements, the algorithm has performed with an improvement of total path length from 13 to 33 percent compared to the PR method
Keywords
Hopfield neural nets; directed graphs; minimisation; Hopfield-type neural network; binary decision neuron model; crossing number minimisation; heuristic methods; hierarchical graph visualization; single phase algorithm; total path length minimisation; Engineering drawings; Hopfield neural networks; Humans; Internet; Minimization methods; Neural networks; Neurons; Quadratic programming; Sun; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-2559-1
Type
conf
DOI
10.1109/ICSMC.1995.538076
Filename
538076
Link To Document