Generative Adversarial Network and Its Application in Energy Internet
نویسندگان
چکیده
Energy Internet (EI) can provide consumers with flexible energy-sharing services. Recently, artificial intelligence (AI) technology has been widely used in the field of EI. Generative adversarial network (GAN) is one hottest research directions AI recent years, and its excellent data generation ability attracted wide attention. First, this paper introduces framework, advantages, disadvantages, improvement classic GAN. Then, application GAN EI reviewed. Finally, summarized, possible prospected.
منابع مشابه
Energy-based Generative Adversarial Network
We introduce the “Energy-based Generative Adversarial Network” model (EBGAN) which views the discriminator as an energy function that associates low energies with the regions near the data manifold and higher energies with other regions. Similar to the probabilistic GANs, a generator is trained to produce contrastive samples with minimal energies, while the discriminator is trained to assign hi...
متن کاملWasserstein Generative Adversarial Network
Recent advances in deep generative models give us new perspective on modeling highdimensional, nonlinear data distributions. Especially the GAN training can successfully produce sharp, realistic images. However, GAN sidesteps the use of traditional maximum likelihood learning and instead adopts an two-player game approach. This new training behaves very differently compared to ML learning. Ther...
متن کاملControllable Generative Adversarial Network
Although it is recently introduced, in last few years, generative adversarial network (GAN) has been shown many promising results to generate realistic samples. However, it is hardly able to control generated samples since input variables for a generator are from a random distribution. Some attempts have been made to control generated samples from GAN, but they have shown moderate results. Furt...
متن کاملGANGs: Generative Adversarial Network Games
Generative Adversarial Networks (GAN) have become one of the most successful frameworks for unsupervised generative modeling. As GANs are difficult to train much research has focused on this. However, very little of this research has directly exploited gametheoretic techniques.We introduce Generative Adversarial Network Games (GANGs), which explicitly model a finite zero-sum game between a gene...
متن کاملCapsuleGAN: Generative Adversarial Capsule Network
We present Generative Adversarial Capsule Network (CapsuleGAN), a framework that uses capsule networks (CapsNets) instead of the standard convolutional neural networks (CNNs) as discriminators within the generative adversarial network (GAN) setting, while modeling image data. We provide guidelines for designing CapsNet discriminators and the updated GAN objective function, which incorporates th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2022
ISSN: ['1026-7077', '1563-5147', '1024-123X']
DOI: https://doi.org/10.1155/2022/9985522