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

Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification

no code implementations • 3 Mar 2020 • Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Sheraz Ahmad, Waqar Mahmood, Andreas Dengel

Second, it investigates the performance impact of traditional machine learning based Urdu text document classification methodologies by embedding 10 filter-based feature selection algorithms which have been widely used for other languages.

Automated Feature Engineering BIG-bench Machine Learning +6