A Bayesian Generative Adversarial Network (GAN) to Generate Synthetic Time-Series Data, Application in Combined Sewer Flow Prediction

no code implementations • 31 Jan 2023 • Amin E. Bakhshipour, Alireza Koochali, Ulrich Dittmer, Ali Haghighi, Sheraz Ahmad, Andreas Dengel

In this study, we developed a GAN model to generate synthetic time series to balance our limited recorded time series data and improve the accuracy of a data-driven model for combined sewer flow prediction.

Data Augmentation Generative Adversarial Network +3