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Parameter identification of complex network dynamics
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DOI：10.1007/s11071-021-06482-4.png)
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摘要
En 中文
Here, we present a novel approach called the parameter identification of complex network dynamics algorithm which combines elements of the sparse identification of nonlinear dynamics algorithm with a genetic algorithm to automatically and efficiently discover the underlying dynamics of complex networks from data with minimal domain-specific knowledge requirements. Testing the proposed algorithm on empirical complex network data verifies the accuracy and efficiency of this method compared to a purely evolutionary approach.
Keyword:
Data-driven methods
Complex networks
Dynamical systems
Machine learning
Evolutionary algorithms
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期刊
IF:
6
论文数:
1.4W
被引数:
4.1W
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