Different Meta-Heuristic Optimized Radial Basis Function Neural Network Models for Short-Term Power Consumption Forecasting
Accurate forecasting of electricity consumption is crucial for refined planning and improved transmission and distribution efficiency. Power consumption data, being nonstationary and nonlinear, is significantly affected by factors such as seasons and holidays, making traditional computational method...
Saved in:
Main Authors: | Dhivagar Shanmugam, V Ramana |
---|---|
Format: | Article |
Language: | English |
Published: |
Bilijipub publisher
2024-06-01
|
Series: | Advances in Engineering and Intelligence Systems |
Subjects: | |
Online Access: | https://aeis.bilijipub.com/article_199135_3b1bc65dac1b0209276a01cae0fd629d.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Investigating the Two Optimization Algorithms (GWO and ACO) Coupling with Radial Basis Neural Network to Estimate the Pile Settlement
by: Ehsanolah Assareh, et al.
Published: (2023-03-01) -
Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms
by: Milad Mohebbi, et al.
Published: (2024-06-01) -
Quality optimization of liquid silicon lenses based on sequential approximation optimization and radial basis function networks
by: Hanjui Chang, et al.
Published: (2025-02-01) -
Photovoltaic Farm Production Forecasting: Modified Metaheuristic Optimized Long Short-Term Memory-Based Networks Approach
by: Aleksandar Stojkovic, et al.
Published: (2025-01-01) -
A Novel Classification of Uncertain Stream Data using Ant Colony Optimization Based on Radial Basis Function
by: Tahsin Ali Mohammed Amin, et al.
Published: (2022-11-01)