Geneticizing input selection based advanced neural network model for sediment prediction in different climate zone
The study focuses on developing an accurate prediction model for suspended sediment load (SSL) based on antecedent SSL and water discharge values. Two Artificial Intelligence (AI) models, Hybrid and Parallel, were employed to test on the Kelantan and Mississippi Rivers in different climate zones and...
Saved in:
Main Authors: | Abdulmohsin Afan H., Hanna Melini Wan Mohtar W., Aksoy M., Najah Ahmed A., Khaleel F., Munir Hayet Khan M., Hatem Kamel A., Sherif M., El-Shafie A. |
---|---|
Other Authors: | 56436626600 |
Format: | Article |
Published: |
Ain Shams University
2025
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of the Whale Optimization Algorithm (WOA) in Reservoir Optimization Operation Under Investigation of Climate Change Impact: A Case Study at Klang Gate Dam, Malaysia
by: Lai V., et al.
Published: (2024) -
Prediction model for spectroscopy using Python programming
by: A. A. M., Ismail, et al.
Published: (2022) -
State of component models usage: Justifying the need for a component model selection framework
by: Aris H., et al.
Published: (2023) -
Adaptive Mechanism for GA-NN to Enhance Prediction Model
by: Faridah Sh Ismail, et al.
Published: (2015) -
Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
by: Marlan Z.M., et al.
Published: (2024)