ISOA‐DBN: A New Data‐Driven Method for Studying the Operating Characteristics of Air Conditioners DOI Creative Commons
Mengran Zhou, Qiqi Zhang, Feng Hu

et al.

Energy Science & Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

ABSTRACT Air conditioning load is a crucial demand response resource for optimizing energy consumption control, and its accurate analysis provides an essential basis achieving efficient management. We aim at solving the problems of scarcity, single type, low accuracy difficult construction high‐quality data sets available air operation characteristic models present. This paper proposes method model based on improved seagull optimization algorithm to optimize deep belief network (ISOA‐DBN). Firstly, set study characteristics obtained through experiments. Secondly, Restricted Boltzmann Machine (RBM) Deep Belief Network (DBN) are used operating conditioning. The results show that effect better when DBN conditioning, coefficient determination reaches 0.9439. Then, SOA improved, performance tested. ISOA performs than in test 14 standard functions. Finally, adjust parameters finely. compared with SOA‐DBN, ISOA‐DBN has conditioners, 0.9534. can provide strong support studying under different working conditions broad application prospects control.

Language: Английский

Topology optimization design and performance analysis of the low resistance rectifier for uniform air supply DOI

Mengfan Quan,

Yu Zhou, Yi Wang

et al.

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: March 11, 2025

Language: Английский

Citations

0
Environmental and Energy Performance Analyses of HVAC Systems in Office Buildings Using Boosted Ensembled Regression Trees: Machine Learning Strategy for Energy Saving of Air Conditioning and Lighting Facilities DOI

Ashraf M. Zaki,

Mohamed E. Zayed, Mohamed H. S. Bargal

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 107214 - 107214

Published: April 1, 2025

Language: Английский

Citations

0
ISOA‐DBN: A New Data‐Driven Method for Studying the Operating Characteristics of Air Conditioners DOI Creative Commons
Mengran Zhou, Qiqi Zhang, Feng Hu

et al.

Energy Science & Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

ABSTRACT Air conditioning load is a crucial demand response resource for optimizing energy consumption control, and its accurate analysis provides an essential basis achieving efficient management. We aim at solving the problems of scarcity, single type, low accuracy difficult construction high‐quality data sets available air operation characteristic models present. This paper proposes method model based on improved seagull optimization algorithm to optimize deep belief network (ISOA‐DBN). Firstly, set study characteristics obtained through experiments. Secondly, Restricted Boltzmann Machine (RBM) Deep Belief Network (DBN) are used operating conditioning. The results show that effect better when DBN conditioning, coefficient determination reaches 0.9439. Then, SOA improved, performance tested. ISOA performs than in test 14 standard functions. Finally, adjust parameters finely. compared with SOA‐DBN, ISOA‐DBN has conditioners, 0.9534. can provide strong support studying under different working conditions broad application prospects control.

Language: Английский

Citations

0