Wei–Neng Chen
Biographic Data
| ID | 8804113 |
|---|---|
| NAME | Wei–Neng Chen |
| GIVEN NAMES | Wei–Neng |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN W N |
| AFFILIATIONS | South China University of Technology |
| ORCID | 0000-0003-0843-5802 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
An Asynchronous Distributed Cooperative Coevolutionary Algorithm for Multilayer Influence Maximization
The influence maximization (IM) problem in large-scale social networks has attracted great attention. Considering the interactions among multiple online social platforms, the multilayer IM problem poses further challenges ( $\rm i.e.,$ high-simulation burden and low-optimization quality). To solve these problems, this article proposes a susceptible-exposed-infected1-infected2-infected12-vigilant (SE3IV) model to simulate the information spreading…
An Individual Evolutionary Game Model Guided by Global Evolutionary Optimization for Vehicle Energy Station Distribution
Collective decision-making problems consisting of individual decisions are commonly seen in social applications. In this article, the vehicle energy station distribution problem (VESDP) is considered, which is modeled as a network-based collective decision-making problem fulfilling consumers’ requirements by arranging the distribution of energy stations rationally. This problem involves the game among the government and energy station investors. …
Uncertain Commuters Assignment Through Genetic Programming Hyper-Heuristic
Traffic assignment problem (TAP) is of great significance for promoting the development of smart city and society. It usually focuses on the deterministic or predictable traffic demand and the vehicle traffic assignment. However, in the real world, traffic demand is usually unpredictable, especially the foot traffic assignment inside buildings such as shopping malls and subway stations. In this work, we consider the dynamic version of TAP, where …
A Max–Min Ant System With Repetitive Influence Reduction Strategy for Interactive Dissemination of Positive and Negative Information
The rapid development of online social networks (OSNs) has facilitated people to express opinions and share information. To optimize the utility of information dissemination in OSNs, problems such as influence maximization have received increasing attention in recent years. However, not only positive information but also negative information is spreading in OSNs. The dissemination of positive and negative information interacts with each other, ma…
Automatic Crowd Navigation Path Planning in Public Scenes Through Multiobjective Differential Evolution
Crowd navigation path planning is important in public scenes. Existing strategies are mainly based on manual design, which is not flexible or effective enough. This article proposes an evolutionary framework for automatic crowd navigation path planning in public scenes. The proposed framework contains a new fitness evaluation mechanism that can quantitatively evaluate the quality of a path planning strategy by considering both crowd safety and fl…
Mining Multiplatform Opinions During Public Health Crisis: A Comparative Study
Emerging infectious diseases pose a growing threat to human society and have sparked extensive public discussions on social media. Although numerous efforts have been made in health data mining on social media, there is a lack of focus on quantitative comparisons across multiple platforms, despite their crucial role in the holistic social communication system. This study addresses this gap by developing a generalized regression model that conside…
Modeling Information Cocoons in Networked Populations: Insights From Backgrounds and Preferences
The formation of information cocoons, driven by limited disclosure and individual preferences, has resulted in the polarization of society. However, the underlying mechanisms and pathways to escape these cocoons remain unresolved. This article aims to solve it by developing an adaptive imitation process. In this process, the measurement of information cocoons across the population is based on Shannon’s information entropy, taking into account nei…
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An Individual Evolutionary Game Model Guided by Global Evolutionary Optimization for Vehicle Energy Station Distribution
Collective decision-making problems consisting of individual decisions are commonly seen in social applications. In this article, the vehicle energy station distribution problem (VESDP) is considered, which is modeled as a network-based collective decision-making problem fulfilling consumers’ requirements by arranging the distribution of energy stations rationally. This problem involves the game among the government and energy station investors. …
Uncertain Commuters Assignment Through Genetic Programming Hyper-Heuristic
Traffic assignment problem (TAP) is of great significance for promoting the development of smart city and society. It usually focuses on the deterministic or predictable traffic demand and the vehicle traffic assignment. However, in the real world, traffic demand is usually unpredictable, especially the foot traffic assignment inside buildings such as shopping malls and subway stations. In this work, we consider the dynamic version of TAP, where …
A Max–Min Ant System With Repetitive Influence Reduction Strategy for Interactive Dissemination of Positive and Negative Information
The rapid development of online social networks (OSNs) has facilitated people to express opinions and share information. To optimize the utility of information dissemination in OSNs, problems such as influence maximization have received increasing attention in recent years. However, not only positive information but also negative information is spreading in OSNs. The dissemination of positive and negative information interacts with each other, ma…
Automatic Crowd Navigation Path Planning in Public Scenes Through Multiobjective Differential Evolution
Crowd navigation path planning is important in public scenes. Existing strategies are mainly based on manual design, which is not flexible or effective enough. This article proposes an evolutionary framework for automatic crowd navigation path planning in public scenes. The proposed framework contains a new fitness evaluation mechanism that can quantitatively evaluate the quality of a path planning strategy by considering both crowd safety and fl…
Mining Multiplatform Opinions During Public Health Crisis: A Comparative Study
Emerging infectious diseases pose a growing threat to human society and have sparked extensive public discussions on social media. Although numerous efforts have been made in health data mining on social media, there is a lack of focus on quantitative comparisons across multiple platforms, despite their crucial role in the holistic social communication system. This study addresses this gap by developing a generalized regression model that conside…
Modeling Information Cocoons in Networked Populations: Insights From Backgrounds and Preferences
The formation of information cocoons, driven by limited disclosure and individual preferences, has resulted in the polarization of society. However, the underlying mechanisms and pathways to escape these cocoons remain unresolved. This article aims to solve it by developing an adaptive imitation process. In this process, the measurement of information cocoons across the population is based on Shannon’s information entropy, taking into account nei…
An Asynchronous Distributed Cooperative Coevolutionary Algorithm for Multilayer Influence Maximization
The influence maximization (IM) problem in large-scale social networks has attracted great attention. Considering the interactions among multiple online social platforms, the multilayer IM problem poses further challenges ( $\rm i.e.,$ high-simulation burden and low-optimization quality). To solve these problems, this article proposes a susceptible-exposed-infected1-infected2-infected12-vigilant (SE3IV) model to simulate the information spreading…
Computer Science (7 works) · Artificial Intelligence (5 works) · Engineering (4 works) · Mathematical optimization (4 works) · Mathematics (4 works) · Complex Network Analysis Techniques (3 works) · Machine learning (3 works) · Opinion Dynamics and Social Influence (3 works) · Distributed computing (2 works) · Genetic algorithm (2 works)