Reconstructing Damaged Complex Networks Based on Neural Networks

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9

초록

Despite recent progress in the study of complex systems, reconstruction of damaged networks due to random and targeted attack has not been addressed before. In this paper, we formulate the network reconstruction problem as an identification of network structure based on much reduced link information. Furthermore, a novel method based on multilayer perceptron neural network is proposed as a solution to the problem of network reconstruction. Based on simulation results, it was demonstrated that the proposed scheme achieves very high reconstruction accuracy in small-world network model and a robust performance in scale-free network model.

키워드

network reconstructionneural networkssmall world networksscale free networksPAPR REDUCTIONSMALL-WORLD
제목
Reconstructing Damaged Complex Networks Based on Neural Networks
저자
Lee, Ye HoonSohn, Insoo
DOI
10.3390/sym9120310
발행일
2017-12
유형
Article
저널명
Symmetry
9
12