Application of Generative Adversarial Network for the Prediction of Gasoline Properties
Near-infrared (NIR) spectroscopy has been widely used to predict the gasoline properties that are difficult to measure online during gasoline blending. NIR models should be prepared in advance to apply this technique successfully. Obtaining a high-accuracy NIR model in practice is hard because abund...
Main Authors: | Kaixun He, Jingjing Liu, Zhi Li |
---|---|
Format: | Article |
Language: | English |
Published: |
AIDIC Servizi S.r.l.
2020-08-01
|
Series: | Chemical Engineering Transactions |
Online Access: | https://www.cetjournal.it/index.php/cet/article/view/11093 |
Similar Items
-
Adversarial Examples Detection for XSS Attacks Based on Generative Adversarial Networks
by: Xueqin Zhang, et al.
Published: (2020-01-01) -
Targeted Speech Adversarial Example Generation With Generative Adversarial Network
by: Donghua Wang, et al.
Published: (2020-01-01) -
Early Action Prediction With Generative Adversarial Networks
by: Dong Wang, et al.
Published: (2019-01-01) -
The Defense of Adversarial Example with Conditional Generative Adversarial Networks
by: Fangchao Yu, et al.
Published: (2020-01-01) -
Semantic Predictive Coding with Arbitrated Generative Adversarial Networks
by: Radamanthys Stivaktakis, et al.
Published: (2020-08-01)