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3 changes: 2 additions & 1 deletion research-studies/ml-problems-techniques-nfv.md
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| Data Synthesis based on Generative Adversarial Networks, 2018 | GAN | Time series Text Data | Generative Adversary Network and LSTM are used in Existing work | https://github.com/mahmoodm2/tableGAN | Most of the data generation is done for images and videos. There is a huge scope for generating synthetic time series data using GAN. |
| Efficient GAN based Anomaly Detection, 2018 | GAN | Time Series Data, KDD Data | https://github.com/houssamzenati/Efficient-GAN-Anomaly-Detection |
| Text Generation With LSTM Recurrent Neural Networks in Python with Keras, 2019 | LSTM | KDD Dataset | https://www.tensorflow.org/text/tutorials/text\_generation |
| Prediction Method of Multiple Related Time Series Based on Generative Adversarial Networks | GRU, LSTM, SVR, MTSGAN | Web Traffic Dataset, NOAA China Dataset | https://github.com/Luoyonghong/Multivariate-Time-Series-Imputation-with-Generative-Adversarial-Networks |
| Prediction Method of Multiple Related Time Series Based on Generative Adversarial Networks | GRU, LSTM, SVR, MTSGAN | Web Traffic Dataset, NOAA China Dataset | https://github.com/Luoyonghong/Multivariate-Time-Series-Imputation-with-Generative-Adversarial-Networks |
| Anomaly Detection of System Logs Based on Natural Language Processing and Deep Learning | Word2vec, Term Frequency-Inverse Document Frequency (TF-IDF), Long Short-Term Memory (LSTM), Gradient Boosting Decision Tree (GBDT), and Naïve Bayes | System logs generated by the Thunderbird supercomputer | https://ieeexplore.ieee.org/abstract/document/8552075 |