Optimizing neural network algorithms for submerged membrane bioreactor: A comparative study of OVAT and RSM hyperparameter optimization techniques

Optimizing neural network algorithms for submerged membrane bioreactor: A comparative study of OVAT and RSM hyperparameter optimization techniques

Hyperparameter tuning is an important process to maximize the performance of any neural network model. This present study proposed the factorial design of experiment for screening and response surface methodology to optimize the hyperparameter of two artificial neural network algorithms. Feed-forwar...

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Bibliographic Details
Main Authors: Syahira Ibrahim, Norhaliza Abdul Wahab
Format: Article
Language:English
Published: IWA Publishing 2024-04-01
Series:Water Science and Technology
Subjects:
computational time
doe implementation
neural network
optimization techniques
submerged membrane bioreactor data
Online Access:http://wst.iwaponline.com/content/89/7/1701

Internet

http://wst.iwaponline.com/content/89/7/1701

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