44 citations · 53 across the 5 of their papers we have counts for
6 papers
Benchmark Functions for CEC 2022 Competition on Seeking Multiple Optima in Dynamic Environments
Wenjian Luo, Xin Lin, Changhe Li +2
Dynamic and multimodal features are two important properties and widely existed in many real-world optimization problems. The former illustrates that the objectives and/or constrai…
ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks
Liang Qu, Huaisheng Zhu, Ruiqi Zheng +2
Imbalanced classification on graphs is ubiquitous yet challenging in many real-world applications, such as fraudulent node detection. Recently, graph neural networks (GNNs) have sh…
Adaptive Coordinated Motion Control for Swarm Robotics Based on Brain Storm Optimization
Jian Yang, Yuhui Shi
Coordinated motion control in swarm robotics aims to ensure the coherence of members in space, i.e., the robots in a swarm perform coordinated movements to maintain spatial structu…
Robotic Brain Storm Optimization: A Multi-target Collaborative Searching Paradigm for Swarm Robotics
Jian Yang, Yuhui Shi
Swarm intelligence optimization algorithms can be adopted in swarm robotics for target searching tasks in a 2-D or 3-D space by treating the target signal strength as fitness value…
Attention-oriented Brain Storm Optimization for Multimodal Optimization Problems
Jian Yang, Yuhui Shi
Population-based methods are often used to solve multimodal optimization problems. By combining niching or clustering strategy, the state-of-the-art approaches generally divide the…
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning
Yurui Ming, Dongrui Wu, Yu-Kai Wang +2
Fatigue is the most vital factor of road fatalities and one manifestation of fatigue during driving is drowsiness. In this paper, we propose using deep Q-learning to analyze an ele…