2021
DOI: 10.1016/j.isci.2021.103420
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Artificial neural network-based smart aerogel glazing in low-energy buildings: A state-of-the-art review

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Cited by 21 publications
(6 citation statements)
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References 97 publications
(183 reference statements)
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“…The study provides an in-depth analysis of the aerogel material, its production, and construction applications. The results show the potential of this material as a promising candidate for the energy efficiency of buildings [29]. Fig.…”
Section: Glazing Of Transparent Constructionsmentioning
confidence: 74%
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“…The study provides an in-depth analysis of the aerogel material, its production, and construction applications. The results show the potential of this material as a promising candidate for the energy efficiency of buildings [29]. Fig.…”
Section: Glazing Of Transparent Constructionsmentioning
confidence: 74%
“…3. Structural configuration of a PCM and aerogel-integrated window glazing system (according to [29]).…”
Section: Glazing Of Transparent Constructionsmentioning
confidence: 99%
“…The third stage is the explosive period, where the average annual publication volume reaches 118.8 articles in the period from 2018-2022. With the increasing requirements of low carbon and environmental protection in the construction industry and the in-depth research on aerogel applications, aerogels in buildings have now also become a research hotspot in the field, and many scholars have started to conduct comprehensive research on the technology, process, evaluation, and influencing factors of aerogels in construction [26][27][28][29][30]. By the third stage, the research of aerogels in the field of construction developed like never before and had a certain system and structure.…”
Section: Publication Trend Analysismentioning
confidence: 99%
“…Recently, there has been increasing interests in advanced energy management strategies using ML methods, such as supervised learning (SL), reinforcement learning (RL), unsupervised learning (UNSL), and semi-supervised learning [22,23]. ML applications mainly include operations, optimization, control, scheduling, and management [24][25][26]. Zhou [27] comprehensively reviewed the applications of AI in carbon neutral and community energy management from the view of energy supply and storage, regional demand, and energy management.…”
Section: Introductionmentioning
confidence: 99%