A multi-factorial evolutionary algorithm concerning diversity information for solving the multitasking Robust Influence Maximization Problem on networks-Reference-Cited by-同舟云学术

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A multi-factorial evolutionary algorithm concerning diversity information for solving the multitasking Robust Influence Maximization Problem on networks

Published:2023-11-16 Issue:1 Volume:35 Page:
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Chen Minghao¹^ORCID,Wang Shuai¹^ORCID,Zhang Jiazhong¹^ORCID

Affiliation:

1. School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, People’s Republic of China

Funder

Shenzhen Science and Technology Program

Fundamental Research Funds for the Central Universities, Sun Yat-sen University

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2275534

Reference57 articles.

1. Optimized Algorithm for Skyline Community Discovery in Multi-Valued Networks

2. Emergence of Scaling in Random Networks

3. A 61-million-person experiment in social influence and political mobilization

4. Maximizing Social Influence in Nearly Optimal Time

5. Optimizing the Robustness of Scale-Free Networks with Simulated Annealing

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1. An online transfer learning based multifactorial evolutionary algorithm for solving the clustered Steiner tree problem;Knowledge-Based Systems;2024-07

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