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This study presents an ensembled method, WTD-GWO-SVR, for predicting dissolved oxygen (DO) levels in aquaculture environments, combining wavelet threshold denoising, grey wolf optimization, and support vector regression. The method addresses challenges such as noise and data quality, achieving high accuracy with mean squared error of 0.38% and R2 value of 99.73%, outperforming traditional models like back-propagation neural networks and long short-term memory models. The results indicate that WTD-GWO-SVR is

Author
meher.woxsen
Language
EN