Daily allocation of energy consumption forecasting of a power distribution company using optimized least squares support vector machine
Accurate energy consumption forecasting is critical for efficient power distribution management. This study presents a novel approach for optimal allocation forecasting of energy consumption in a power distribution company, utilizing the Least Squares Support Vector Machine (LSSVM) optimized by nove...
Saved in:
Main Authors: | Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Mohammad Bin Amin |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-03-01
|
Series: | Results in Control and Optimization |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666720725000049 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
METHOD OF DEGRADATION DATA RELIABILITY EVALUATION BASED ON THE LEAST SQUARE SUPPORT VECTOR MACHINE
by: FENG Shuai, et al.
Published: (2016-01-01) -
Least square-based vehicle position estimation algorithm
by: PENG Xin, et al.
Published: (2010-01-01) -
Study on Taidonghe River Daily Flow Prediction with Genetic Algorithm and Least Squares Support Vector Machine
by: HANG Qing-feng, et al.
Published: (2010-01-01) -
State Estimation in Power Systems Under False Data Injection Attack Using Total Least Squares
by: Bamrung Tausiesakul, et al.
Published: (2025-01-01) -
Direct Interval Prediction of Landslide Displacements Using Least Squares Support Vector Machines
by: Yankun Wang, et al.
Published: (2020-01-01)