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Huiheng Liu, Jinrui Liang, Yanchen Liu and Huijun Wu
Building energy consumption prediction has a significant effect on energy control, design optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID-19 in buildings, providing a guarantee for energy efficiency and carbo...
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Zeqin Tian, Dengfeng Chen and Liang Zhao
Accurate building energy consumption prediction is a crucial condition for the sustainable development of building energy management systems. However, the highly nonlinear nature of data and complex influencing factors in the energy consumption of large ...
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Sanguk Park
This study aims to enable cost-effective Internet of Things (IoT) system design by removing redundant IoT sensors through the correlation analysis of sensing data collected in a smart home environment. This study also presents a data analysis and predict...
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Jiaqi Yu, Wen-Shao Chang and Yu Dong
Building energy usage has been an important issue in recent decades, and energy prediction models are important tools for analysing this problem. This study provides a comprehensive review of building energy prediction models and uncertainties in the mod...
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Yu Cui, Zishang Zhu, Xudong Zhao, Zhaomeng Li and Peng Qin
Conventional building energy models (BEM) for heating and cooling energy-consumption prediction without calibration are not accurate, and the commonly used manual calibration method requires the high expertise of modelers. Bayesian calibration (BC) is a ...
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Maha Alanbar,Amal Alfarraj,Manal Alghieth
Pág. pp. 166 - 177
In the present era, due to technological advances, the problem of energy consumption has become one of the most important problems for its environmental and economic impact. Educational buildings are one of the highest energy consuming institutions. Ther...
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Building Energy and Comfort Management (BECM) systems have the potential to considerably reduce costs related to energy consumption and improve the efficiency of resource exploitation, by implementing strategies for resource management and control and po...
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Hamid R. Khosravani, María Del Mar Castilla, Manuel Berenguel, Antonio E. Ruano and Pedro M. Ferreira
Energy consumption has been increasing steadily due to globalization and industrialization. Studies have shown that buildings are responsible for the biggest proportion of energy consumption; for example in European Union countries, energy consumption in...
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Yaolin Lin, Jingye Liu, Kamiel Gabriel, Wei Yang and Chun-Qing Li
Buildings consume about 40% of the global energy. Building energy consumption is affected by multiple factors, including building physical properties, performance of the mechanical system, and occupants? activities. The prediction of building energy cons...
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Zhijing Ye, Zheng O?Neill and Fei Hu
Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors? data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber...
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Guwon Yoon, Seunghwan Kim, Haneul Shin, Keonhee Cho, Hyeonwoo Jang, Tacklim Lee, Myeong-in Choi, Byeongkwan Kang, Sangmin Park, Sanghoon Lee, Junhyun Park, Hyeyoon Jung, Doron Shmilovitz and Sehyun Park
Energy prediction models and platforms are being developed to achieve carbon-neutral ESG, transition buildings to renewable energy, and supply sustainable energy to EV charging infrastructure. Despite numerous studies on machine learning (ML)-based predi...
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Amany Khalil, Anas M. Hosney Lila and Nouran Ashraf
The climate change crisis has resulted in the need to use sustainable methods in architectural design, including building form and orientation decisions that can save a significant amount of energy consumed by a building. Several previous studies have op...
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Yifan Cao, Yangda Chen, Mingwen Shi, Chuanzhen Li, Weijun Wu, Yapeng Li, Xuxin Guo and Xianpeng Sun
The high energy consumption CEA building brings challenges to the management of the energy system. An accurate energy consumption prediction model is necessary. Although there are various prediction methods, the prediction method for the particularity of...
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Wei Yu, Baizhan Li, Yarong Lei and Meng Liu
In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption dem...
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Yafei Zhao, Paolo Vincenzo Genovese and Zhixing Li
With the improvement of technologies, people?s demand for intelligent devices of indoor and outdoor living environments keeps increasing. However, the traditional control system only adjusts living parameters mechanically, which cannot better meet the re...
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Tara L. Cavalline, Jorge Gallegos, Reid W. Castrodale, Charles Freeman, Jerry Liner and Jody Wall
Due to their porous nature, lightweight aggregates have been shown to exhibit thermal properties that are advantageous when used in building materials such as lightweight concrete, grout, mortar, and concrete masonry units. Limited data exist on the ther...
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Nashwan Dawood
Load forecasting plays a major role in determining the prices of the energy supplied to end customers. An accurate prediction is vital for the energy companies, especially when it comes to the baseline calculations that are used to predict the energy loa...
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Lara Ramadan, Isam Shahrour, Hussein Mroueh and Fadi Hage Chehade
Improving the energy efficiency of the building sector has become an increasing concern in the world, given the alarming reports of greenhouse gas emissions. The management of building energy systems is considered an essential means for achieving this go...
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Bruno Mataloto, Hugo Mendes and Joao C. Ferreira
People in shared building space have an important role in energy consumption because they can turn on/off equipment and heat/cooling systems. This behaviour can be influenced by giving then locally tailored context information (energy consumption, temper...
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Noriyuki Kushiro, Ami Fukuda, Masatada Kawatsu and Toshihiro Mega
In this study, methods for predicting energy demand on hourly consumption data are established for realizing an energy management system for buildings. The methods consist of an energy prediction algorithm that automatically separates the datasets to par...
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