Reconstructing Damaged Complex Networks Based on Neural Networks

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.

• Publication year

  2017

• Venue

  Symmetry

• Publication date

  2017-12-09

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.3390/sym9120310
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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