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- W2726307716 abstract "Existing studies indicated that it is crucial to design network structures with well tolerance against potential attacks and failures in reality, and several attack models have been proposed and lucubrated. Aiming at enhancing network robustness suffering from edge-based attack cascading failures, we first propose a measure, R <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>ce</sub> , to numerically evaluate the robustness of networks under cascading failures, and then a memetic algorithm, termed as MA-R <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>ce</sub> , is devised to optimize network robustness without changing the degree distribution. The experimental results on synthetic and real-world networks show that MA-R <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>ce</sub> can provide candidate networks with better anti-attack performance initialized by an initial network, also outperforms exist heuristic optimization algorithm, which facilitates theoretic analyses and provides potential solutions to realistic dilemmas in networked systems for decision makers." @default.
- W2726307716 created "2017-07-14" @default.
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- W2726307716 date "2017-06-01" @default.
- W2726307716 modified "2023-09-24" @default.
- W2726307716 title "Enhancing the robustness of complex networks against edge-based-attack cascading failures" @default.
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- W2726307716 doi "https://doi.org/10.1109/cec.2017.7969291" @default.
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