A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. Real-world optimizations, such as forecasting streamflow, are a complicated process that is highly non-linear and mu...
Saved in:
Main Author: | Wei , Yaxing |
---|---|
Format: | Thesis |
Published: |
2024
|
Subjects: | |
Online Access: | http://studentsrepo.um.edu.my/15404/1/Wei_Yaxing.pdf http://studentsrepo.um.edu.my/15404/2/Wei_Yaxing.pdf http://studentsrepo.um.edu.my/15404/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
by: YAXING, WEI, et al.
Published: (2024) -
Comparative analysis of artificial intelligence methods for streamflow forecasting
by: Wei, Yaxing, et al.
Published: (2024) -
Investigation of meta-heuristics algorithms in ANN streamflow forecasting
by: Wei, Yaxing, et al.
Published: (2023) -
A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting
by: Ibrahim, Karim Sherif Mostafa Hassan, et al.
Published: (2022) -
State-of-the-art development of two-waves artificial intelligence modeling techniques for river streamflow forecasting
by: Tan, Woon Yang, et al.
Published: (2022)