Swinburne
Browse

Future Weir Water Level Forecasting using Novel Neural Network Considering Climate Change Impacts

Download (16.03 MB)
thesis
posted on 2024-08-20, 07:36 authored by Louis Yeow Haur Teng

This research developed two novel neural network models, Salp Swarm Optimisation Neural Network (SSONN) and Whale Optimisation Neural Network (WONN), to predict daily water level at Batu Kitang Submersible Weir accurately. Using data from 2001 to 2021, these novel models significantly outperformed conventional neural network models in short-term forecasting. The study also extended to predict long-term water level up to 2100, emphasizing the need for improved water management strategies to address potential flooding risks due to climate change. This work enhanced water resource planning and flood mitigation, offering robust tools for future environmental management.

History

Thesis type

  • Thesis (PhD)

Thesis note

Thesis submitted for the Degree of Doctor of Philosophy, Swinburne University of Technology, Sarawak 2024.

Copyright statement

Copyright © 2024 Louis Yeow Haur Teng.

Supervisors

Kelvin Kuok King Kuok

Language

eng

Usage metrics

    Theses

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC