A binary hopfield neural-network approach for satellite broadcast scheduling problems

被引：20
|
作者：
Funabiki, N
Nishikawa, S
机构：
[1] Department of Information and Computer Sciences, Faculty of Engineering Science, Osaka University, Toyonaka
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1997年 / 8卷 / 02期
关键词：
binary neuron; combinatorial optimization; heuristic method; neural network; parallel computation; satellite broadcast scheduling; simulation;
D O I：
10.1109/72.557699
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a binary Hopfield neural network approach for finding a broadcasting schedule in a low-altitude satellite system. Our neural network is composed of simple binary neurons on the synchronous parallel computation, which is greatly suitable for implementation on a digital machine. With the help of heuristic methods, the neural network of a maximum of 200 000 neurons can always find near-optimum solutions on a conventional work station in our simulations.
引用
收藏
页码：441 / 445
页数：5
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