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• W4313890087 startingPage "321" @default.
• W4313890087 abstract "Complex network science is an interdisciplinary field of study based on graph theory, statistical mechanics, and data science. With the powerful tools now available in complex network theory for the study of network topology, it is obvious that complex network topology models can be applied to enhance artificial neural network models. In this paper, we provide an overview of the most important works published within the past 10 years on the topic of complex network theory-based optimization methods. This review of the most up-to-date optimized neural network systems reveals that the fusion of complex and neural networks improves both accuracy and robustness. By setting out our review findings here, we seek to promote a better understanding of basic concepts and offer a deeper insight into the various research efforts that have led to the use of complex network theory in the optimized neural networks of today." @default.
• W4313890087 created "2023-01-10" @default.
• W4313890087 creator A5048858559 @default.
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• W4313890087 date "2023-01-07" @default.
• W4313890087 modified "2023-10-05" @default.
• W4313890087 title "Neural Network Optimization Based on Complex Network Theory: A Survey" @default.
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• W4313890087 doi "https://doi.org/10.3390/math11020321" @default.
• W4313890087 hasPublicationYear "2023" @default.
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