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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-12-01
|
| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/9/12/310 |
| _version_ | 1798038337136623616 |
|---|---|
| author | Ye Hoon Lee Insoo Sohn |
| author_facet | Ye Hoon Lee Insoo Sohn |
| author_sort | Ye Hoon Lee |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T21:38:49Z |
| format | Article |
| id | doaj.art-d03e17cb979842349d91464cf9aadcfa |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-11T21:38:49Z |
| publishDate | 2017-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-d03e17cb979842349d91464cf9aadcfa2022-12-22T04:01:40ZengMDPI AGSymmetry2073-89942017-12-0191231010.3390/sym9120310sym9120310Reconstructing Damaged Complex Networks Based on Neural NetworksYe Hoon Lee0Insoo Sohn1Department of Electronic and IT Media Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaDivision of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, KoreaDespite 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.https://www.mdpi.com/2073-8994/9/12/310network reconstructionneural networkssmall world networksscale free networks |
| spellingShingle | Ye Hoon Lee Insoo Sohn Reconstructing Damaged Complex Networks Based on Neural Networks Symmetry network reconstruction neural networks small world networks scale free networks |
| title | Reconstructing Damaged Complex Networks Based on Neural Networks |
| title_full | Reconstructing Damaged Complex Networks Based on Neural Networks |
| title_fullStr | Reconstructing Damaged Complex Networks Based on Neural Networks |
| title_full_unstemmed | Reconstructing Damaged Complex Networks Based on Neural Networks |
| title_short | Reconstructing Damaged Complex Networks Based on Neural Networks |
| title_sort | reconstructing damaged complex networks based on neural networks |
| topic | network reconstruction neural networks small world networks scale free networks |
| url | https://www.mdpi.com/2073-8994/9/12/310 |
| work_keys_str_mv | AT yehoonlee reconstructingdamagedcomplexnetworksbasedonneuralnetworks AT insoosohn reconstructingdamagedcomplexnetworksbasedonneuralnetworks |