Metaheuristic Algorithms to Enhance the Performance of a Feedforward Neural Network in Addressing Missing Hourly Precipitation

Metaheuristic Algorithms to Enhance the Performance of a Feedforward Neural Network in Addressing Missing Hourly Precipitation

This research study investigates the implementation of three metaheuristic algorithms, namely, Grey Wolf Optimizer (GWO), Multi-Verse Optimizer (MVO), and Moth-Flame Optimisation (MFO), for coupling with a Feedforward Neural Network (FNN) in addressing missing hourly rainfall observations, while ove...

Full description

Saved in:
Bibliographic Details
Main Authors: Lai, Wai Yan, Kuok, King Kuok, Shirley, Gato-Trinidad, Md. Rezaur, Rahman, Muhammad Khusairy, Bakri
Format: Article
Language:English
Published: Penerbit UTHM 2023
Subjects:
TP Chemical technology
Online Access:http://ir.unimas.my/id/eprint/44780/1/Metaheuristic%20Algorithms.pdf
http://ir.unimas.my/id/eprint/44780/
https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/8725
https://doi.org/10.30880/ijie.2023.15.01.025
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Malaysia Sarawak
Language: English

Internet

http://ir.unimas.my/id/eprint/44780/1/Metaheuristic%20Algorithms.pdf
http://ir.unimas.my/id/eprint/44780/
https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/8725
https://doi.org/10.30880/ijie.2023.15.01.025

Similar Items