COMPARATIVE STUDY OF SURROGATE TECHNIQUES FOR HYPERPARAMETER OPTIMIZATION IN RECURRENT NEURAL NETWORK

• Main Author: HILMI, MUHAMMAD ZAHID
• Format: Thesis
• Language: English
• Published: 2023
• Subjects: T Technology (General)
• Online Access: http://utpedia.utp.edu.my/id/eprint/24854/1/2023_PhD%20in%20IT_thesis%20submission_1900298_Muhammad%20Zahid%20bin%20Hilmi.pdf; http://utpedia.utp.edu.my/id/eprint/24854/

Long Short-Term Memory (LSTM) models are a type of recurrent neural network (RNN) well-suited for tasks requiring the model to remember long-term dependencies. This makes them a promising approach for ET rate estimation, as ET is a process that is influenced by various factors that may occur over lo...