Prediction of energy consumption in four sectors using support vector regression optimized with genetic algorithm
Effectively managing and optimizing energy resources to accommodate population growth while minimizing carbon emissions has become increasingly intricate. A proficient approach to this dilemma is accurately predicting energy usage and emissions across diverse sectors. This paper unveils a genetic al...
Saved in:
Main Authors: | Md. Sadikul Hasan, Md. Tarequzzaman, Md. Moznuzzaman, Md Abdul Ahad Juel |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Heliyon |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025001458 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm
by: Baraa Yousif Salman, et al.
Published: (2024-09-01) -
The growth–environment nexus amid geopolitical risks: cointegration and machine learning algorithm approaches
by: Md. Idris Ali, et al.
Published: (2025-02-01) -
Daily allocation of energy consumption forecasting of a power distribution company using optimized least squares support vector machine
by: Marzia Ahmed, et al.
Published: (2025-03-01) -
LIFE CYCLE ENERGY CONSUMPTION AND CO2 EMISSIONS OF DIFFERENT CAR TYPES
by: Rosen IVANOV, et al.
Published: (2023-09-01) -
Energy consumption and carbon emissions of mixing plant in asphalt pavement construction with a case study in China and reduction measures
by: Yixuan Liu, et al.
Published: (2025-07-01)