A General Neural Network Model for Estimating Telecommunications Network Reliability

被引:49
作者
Altiparmak, Fulya [3 ]
Dengiz, Berna [1 ]
Smith, Alice E. [2 ]
机构
[1] Baskent Univ, Dept Ind Engn, Fac Engn, TR-06490 Ankara, Turkey
[2] Auburn Univ, Dept Ind & Syst Engn, Auburn, AL 36849 USA
[3] Univ Pittsburgh, Pittsburgh, PA 15260 USA
基金
美国国家科学基金会;
关键词
All-terminal network reliability; estimation; neural network; VARIANCE; DESIGN; BIAS;
D O I
10.1109/TR.2008.2011854
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper puts forth a new encoding method for using neural network models to estimate the reliability of telecommunications networks with identical link reliabilities. Neural estimation is computationally speedy, and can be used during network design optimization by an iterative algorithm such as tabu search, or simulated annealing. Two significant drawbacks of previous approaches to using neural networks to model system reliability are the long vector length of the inputs required to represent the network link architecture, and the specificity of the neural network model to a certain system size. Our encoding method overcomes both of these drawbacks with a compact, general set of inputs that adequately describe the likely network reliability. We computationally demonstrate both the precision of the neural network estimate of reliability, and the ability of the neural network model to generalize to a variety of network sizes, including application to three actual large scale communications networks.
引用
收藏
页码:2 / 9
页数:8
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