A Co-Evolution Algorithm With Dueling Reinforcement Learning Mechanism for the Energy-Aware Distributed Heterogeneous Flexible Flow-Shop Scheduling …
F Zhao, F Yin, L Wang, Y Yu - IEEE Transactions on Systems …, 2024 - ieeexplore.ieee.org
The production process of steelmaking continuous casting (SCC) is a typical heterogeneous
distributed manufacturing system. The scheduling problem in heterogeneous distributed …
distributed manufacturing system. The scheduling problem in heterogeneous distributed …
Collaborative-GAN: An approach for stabilizing the training process of generative adversarial network
Generative Adversarial Network (GAN) outperforms its peers in the generative models'
family and is widely used to generate realistic samples in various domains. The basic idea of …
family and is widely used to generate realistic samples in various domains. The basic idea of …
Multi-objective evolutionary GAN for tabular data synthesis
Synthetic data has a key role to play in data sharing by statistical agencies and other
generators of statistical data products. Generative Adversarial Networks (GANs), typically …
generators of statistical data products. Generative Adversarial Networks (GANs), typically …
MRD‐GAN: Multi‐representation discrimination GAN for enhancing the diversity of the generated data
The generative adversarial network (GAN) is a highly effective member of the generative
models category and is extensively employed for generating realistic samples across …
models category and is extensively employed for generating realistic samples across …
Multi-GANs with Shared Generator: An Approach for Handling Mode Collapse Issue
The Generative Adversarial Network (GAN) is a highly effective member of the generative
models' category and is widely utilized for generating realistic samples across various …
models' category and is widely utilized for generating realistic samples across various …
[CITATION][C] Architecture Knowledge Distillation for Evolutionary Generative Adversarial Network
Generative Adversarial Networks (GANs) are effective for image generation, but their
unstable training limits broader applications. Additionally, neural architecture search (NAS) …
unstable training limits broader applications. Additionally, neural architecture search (NAS) …