Probabilistic Forecasting of Sensory Data With Generative Adversarial Networks – ForGAN

Probabilistic Forecasting of Sensory Data With Generative Adversarial Networks – ForGAN

Time series forecasting is one of the challenging problems for humankind. The traditional forecasting methods using mean regression models have severe shortcomings in reflecting real-world fluctuations. While new probabilistic methods rush to rescue, they fight with technical difficulties like quant...

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Bibliographic Details
Main Authors: Alireza Koochali, Peter Schichtel, Andreas Dengel, Sheraz Ahmed
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Time-series
generative adversarial networks
forecasting
probabilistic
prediction
Online Access:https://ieeexplore.ieee.org/document/8717640/

Internet

https://ieeexplore.ieee.org/document/8717640/

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