Artificial Intelligence Generated Synthetic Datasets as the Remedy for Data Scarcity in Water Quality Index Estimation-Reference-Cited by-同舟云学术

Artificial Intelligence Generated Synthetic Datasets as the Remedy for Data Scarcity in Water Quality Index Estimation

Published:2023-10-28 Issue:15 Volume:37 Page:6183-6198
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Chia Min Yan,Koo Chai Hoon^ORCID,Huang Yuk Feng,Di Chan Wei,Pang Jia Yin

Funder

Universiti Tunku Abdul Rahman

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11269-023-03650-6.pdf

Reference21 articles.

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2. Bertholdo L, Silva D, De Aragão Umbuzeiro CG, G. and, Camolesi Júnior L (2017) Classification, Association and Clustering of Water Body Data: application to Water Quality Monitoring. Environ Processes 4:813–831

3. Bourou S, El Saer A, Velivassaki T-H, Voulkidis A, Zahariadis T (2021) A review of Tabular Data Synthesis using GANs on an IDS dataset. Information 12:375

4. Cinquini M, Giannotti F, Guidotti R (2021) Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery. In: IEEE Third International Conference on Cognitive Machine Intelligence (CogMI), 2021. Atlanta, USA. Institute of Electrical and Electronics Engineers, 54–63

5. Hong D, Baik C (2021) Generating and validating synthetic training data for predicting bankruptcy of individual businesses. J Inform Communication Convergence Eng 19:228–233

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