แจ้งเอกสารไม่ครบถ้วน, ไม่ตรงกับชื่อเรื่อง หรือมีข้อผิดพลาดเกี่ยวกับเอกสาร ติดต่อที่นี่ ==>
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
Prasit Nangtin. Optimizing energy management and reducing peak demand in buildings using forecasting models, machine learning, factorial design, and least squares method. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2025.
Optimizing energy management and reducing peak demand in buildings using forecasting models, machine learning, factorial design, and least squares method
Name: Kittipong Sriamad
Organization :
Pathumwan Institute of Technology. Department of Electrical Engineering
Email :
kittipong.sri@pit.ac.th
Name: Prasit Nangtin
Organization :
Pathumwan Institute of Technology. Department of Electrical Engineering
Email :
prasit@pit.ac.th
LCSH:
Energy consumption
-- Forecasting
LCSH:
Buildings
-- Energy conservation
LCSH:
Machine learning
LCSH:
Least squares
LCSH:
Experimental design
Abstract:
This research focuses on optimizing energy management and reducing peak demand in buildings through the integration of forecasting models, machine learning, factorial design, and the least squares method. By leveraging data-driven techniques, the study aims to predict energy consumption patterns and identify the factors that influence peak demand. Machine learning algorithms are employed to enhance the accuracy of energy usage forecasts, while factorial design aids in analyzing the interactions between various factors affecting energy consumption. Additionally, the least squares method is utilized to refine model predictions and optimize energy efficiency strategies. The goal is to develop a comprehensive approach that minimizes energy consumption during peak periods, leading to cost savings and improved sustainability in building energy management systems
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2025
Modified:
2025-06-18
Issued:
2025-06-18
BibliograpyCitation :
In Electrical Engineering Academic Association (Thailand) and King Mongkut's University of Technology North Bangkok. Department of Electrical and Computer Engineering. 13th International Electrical Engineering Congress (iEECON 2025) (P06269). Bangkok : Electrical Engineering Academic Association (Thailand), 2025
eng
©copyrights
RightsAccess:
ใช้เวลา
0.021286 วินาที
Kittipong Sriamad
| Title | Contributor | Type |
|---|---|---|
| Developing smart iot systems to control peak demand energy using ESP8266 for split type air conditioners
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kittipong Sriamad;Prasit Nangtin | บทความ/Article | |
| Improving the efficiency of short-term load forecasting using fuzzy optimization combined with load feature recognition
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kittipong Sriamad;Weeragul Pratumgul;Sucheera Phramala | บทความ/Article | |
| Optimizing energy management and reducing peak demand in buildings using forecasting models, machine learning, factorial design, and least squares method
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kittipong Sriamad;Prasit Nangtin | บทความ/Article |
Prasit Nangtin
| Title | Contributor | Type |
|---|