
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 27, 2024
Language: Английский
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 27, 2024
Language: Английский
Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41765 - e41765
Published: Jan. 1, 2025
Effectively managing and optimizing energy resources to accommodate population growth while minimizing carbon emissions has become increasingly intricate. A proficient approach this dilemma is accurately predicting usage across diverse sectors. This paper unveils a genetic algorithm (GA)-optimized support vector regression (SVR) model designed (i) predict electricity generation, (ii) consumption in four primary sectors—residential, industrial, commercial, agricultural, (iii) estimate sector-specific emissions. The proposed model's efficacy assessed by calculating the R2 value, mean absolute error (MAE), root squared (RMSE), residual plot. achieved high accuracy with an MAE of 1.18 %, yielded reliable sectoral predictions, reflected values 1.22 % (residential), 4.98 (industrial), 4.40 (commercial), 4.04 (agricultural). residuals exhibited homoscedasticity, value approached one. predicts that 2027, residential sector will consume 55748.66 GWh energy, commercial 14892.49 GWh, industrial 32642.35 agricultural 2288.37 GWh. It been predicted these sectors release 75437.96-billion-gram equivalents.
Language: Английский
Citations
1Clean Technologies and Environmental Policy, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 29, 2025
Language: Английский
Citations
0Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135453 - 135453
Published: March 1, 2025
Language: Английский
Citations
0International Journal of Energy Sector Management, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 7, 2024
Purpose Previous studies emphasized the substantial energy-saving potential of light emitting diode (LED) lighting systems, especially in clothing industry. However, specific quantification energy conservation industrial factories, particularly Bangladesh’s readymade garment (RMG) sector, remains unexplored. The purpose this study is to investigate savings and efficiency improvements systems RMG sector using LED technology. Design/methodology/approach Understanding optimizing consumption crucial because contributes significantly country’s export earnings. For this, an factory was surveyed possible system retrofitting estimated compared. Findings adoption energy-efficient options, LED, could decrease current usage from 15% 7.5% Bangladesh. First, reveals, that reduction annual determined be 18,220 kWh due with tube. Second, it conducts real-time measurements assess suitability in-building providing insights into scenario. Lastly, evaluates economic environmental benefits proposed industries. Due system, equivalent CO 2 gas emissions found 119.896 tCO . Originality/value first time, explored for enhancing design through industry, a focus on By addressing these aspects, aims contribute advancement efforts ultimately fostering sustainable development Bangladesh beyond.
Language: Английский
Citations
1Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 27, 2024
Language: Английский
Citations
0