Resilience of weighted networks with dynamical behavior against multi-node removal
Ziwei Yuan1,2, Changchun Lv3, Dongli Duan3
1School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Chaos (Woodbury, N.Y.)
|September 3, 2024
Summary
This study simplifies complex weighted networks using dimension reduction. It reveals that for epidemic systems, higher weights increase network resilience, unlike other systems studied.
Area of Science:
- Network science
- Complex systems analysis
- Dynamical systems theory
Background:
- Real-world networks often have weighted interactions, crucial for understanding system behavior.
- These weighted networks are vulnerable to cascading failures from minor perturbations.
- Predicting the behavior of multi-dimensional weighted systems is computationally challenging.
Purpose of the Study:
- To develop a dimension reduction technique for analyzing multi-dimensional weighted network dynamics.
- To investigate the impact of interaction weights on the resilience of four distinct dynamical systems.
- To understand how different weight assignment methods influence network resilience.
Main Methods:
- Proposed a dimension reduction technique to simplify multi-dimensional systems into a one-dimensional state space.
- Applied the technique to four dynamical systems: biochemical (B), epidemic (E), regulatory (R), and birth-death (BD).
- Examined the correlation between network weights and system activities under various weight assignment methods.
Main Results:
- For biochemical (B) systems, weights negatively correlate with network activity.
- For epidemic (E), regulatory (R), and birth-death (BD) systems, weights positively correlate with network activity.
- Epidemic (E) systems demonstrate increased resilience with greater weights, while B, R, and BD systems show minimal impact from weight changes.
Conclusions:
- Dimension reduction effectively simplifies the analysis of weighted network resilience.
- Weight-resilience relationships vary significantly across different types of dynamical systems.
- The epidemic system's resilience is positively and significantly influenced by interaction weights.
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