Prediction of Aquatic Ecosystem Health Indices through Machine Learning Models Using the WGAN-Based Data Augmentation Method

Prediction of Aquatic Ecosystem Health Indices through Machine Learning Models Using the WGAN-Based Data Augmentation Method

Changes in hydrological characteristics and increases in various pollutant loadings due to rapid climate change and urbanization have a significant impact on the deterioration of aquatic ecosystem health (AEH). Therefore, it is important to effectively evaluate the AEH in advance and establish appro...

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Bibliographic Details
Main Authors: Seoro Lee, Jonggun Kim, Gwanjae Lee, Jiyeong Hong, Joo Hyun Bae, Kyoung Jae Lim
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Sustainability
Subjects:
aquatic ecosystem health
machine learning models
WGAN
data augmentation
Online Access:https://www.mdpi.com/2071-1050/13/18/10435

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