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Your search keyword '"Gao, Shupeng"' showing total 26 results
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26 results on '"Gao, Shupeng"'

4. A Novel Ant Colony Optimization Algorithm with Dynamic Control Population for Community Detecting

Author

Chen, Jianjun, Gao, Shupeng, Su, Zhen, Chen, Siqi, Li, Xianghua, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Liu, Yong, editor, Wang, Lipo, editor, Zhao, Liang, editor, and Yu, Zhengtao, editor

Published
2020
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18. Target patterns and and numerical algorithm for solving optimal-control problem from Optimal control of networked reaction���diffusion systems

Author

Gao, Shupeng, Chang, Lili, Romi��, Ivan, Wang, Zhen, Jusup, Marko, and Holme, Petter

Abstract

Patterns in nature are fascinating both aesthetically and scientifically. Alan Turing���s celebrated reaction���diffusion model of pattern formation from the 1950s has been extended to an astounding diversity of applications: from cancer medicine, via nanoparticle fabrication, to computer architecture. Recently, several authors have studied pattern formation in underlying networks, but thus far, controlling a reaction���diffusion system in a network to obtain a particular pattern has remained elusive. We present a solution to this problem in the form of an analytical framework and numerical algorithm for optimal control of Turing patterns in networks. We demonstrate our method���s effectiveness and discuss factors that affect its performance. We also pave the way for multidisciplinary applications of our framework beyond reaction���diffusion models.

Published
2022
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26. Optimal control of the reaction-diffusion process on directed networks.

Author

Liu C, Gao S, Song M, Bai Y, Chang L, and Wang Z

Subjects
Humans, Diffusion
Abstract

Reaction-diffusion processes organized in networks have attracted much interest in recent years due to their applications across a wide range of disciplines. As one type of most studied solutions of reaction-diffusion systems, patterns broadly exist and are observed from nature to human society. So far, the theory of pattern formation has made significant advances, among which a novel class of instability, presented as wave patterns, has been found in directed networks. Such wave patterns have been proved fruitful but significantly affected by the underlying network topology, and even small topological perturbations can destroy the patterns. Therefore, methods that can eliminate the influence of network topology changes on wave patterns are needed but remain uncharted. Here, we propose an optimal control framework to steer the system generating target wave patterns regardless of the topological disturbances. Taking the Brusselator model, a widely investigated reaction-diffusion model, as an example, numerical experiments demonstrate our framework's effectiveness and robustness. Moreover, our framework is generally applicable, with minor adjustments, to other systems that differential equations can depict.

Published
2022
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