Graph coloring using fuzzy controlled Neural Networks

被引：0

作者：

Dalianis, P ^{[1
]}

Kitsios, Y ^{[1
]}

Tzafestas, S ^{[1
]}

机构：

[1] Natl Tech Univ Athens, Dept Elect & Comp Engn, Intelligent Robot & Automat Lab, GR-15773 Athens, Greece

来源：

INTELLIGENT AUTOMATION AND SOFT COMPUTING | 1998年 / 4卷 / 04期

关键词：

graph coloring; neural networks; fuzzy controlled neural network; neurofuzzy k-coloring algorithms;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Graph coloring is an important example of a class of combinatorial optimization problems, which are characterized by their large number of interacting degrees of freedom. Neural Networks (NN) and especially a variation of the Hopfield one constitutes a very popular approach to the solution of problems in this class. The algorithm presented here is based on the idea of improving the convergence performance of such a NN, with the use of a simple fuzzy controller. The algorithm is explained and applied to two graphs of different size. The simulation results are presented and described in detail.

引用

页码：273 / 288

页数：16

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