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AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
[HTML][HTML] Energetics Systems and artificial intelligence: Applications of industry 4.0
Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …
reliability, selection, and dynamic response of the power system is essential. Governments …
Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
Artificial Intelligence and emerging digital technologies in the energy sector
Digitalization is an increasingly important direction of energy innovation moving forward.
Nevertheless, which emerging digital technology is more crucial during the energy sector …
Nevertheless, which emerging digital technology is more crucial during the energy sector …
A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects
Abstract The17 Sustainable Development Goals (SDGs) established by the United Nations
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
[HTML][HTML] Renewable energy and sustainable agriculture: Review of indicators
Sustainable agriculture strives to ensure future food and energy supply while safeguarding
natural resources. The interpretation of sustainability varies by context and country, yielding …
natural resources. The interpretation of sustainability varies by context and country, yielding …
Highly imbalanced fault diagnosis of gas turbines via clustering-based downsampling and deep siamese self-attention network
For highly reliable gas turbines that rarely suffer faults, the overwhelming majority of
historical data are collected under healthy state, while only a very small number of them are …
historical data are collected under healthy state, while only a very small number of them are …
Data-driven approach for fault detection and diagnostic in semiconductor manufacturing
SKS Fan, CY Hsu, DM Tsai, F He… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Fault detection and classification (FDC) is important for semiconductor manufacturing to
monitor equipment's condition and examine the potential cause of the fault. Each equipment …
monitor equipment's condition and examine the potential cause of the fault. Each equipment …
Rapid prediction of urban flood based on disaster-breeding environment clustering and Bayesian optimized deep learning model in the coastal city
H Wang, S Xu, H Xu, Z Wu, T Wang, C Ma - Sustainable Cities and Society, 2023 - Elsevier
Rapid prediction of urban flood is essential for sustainable city and society development.
The data-driven deep learning model is commonly adopted for flood prediction, but it rarely …
The data-driven deep learning model is commonly adopted for flood prediction, but it rarely …
Exploratory policy analysis for electric vehicle adoption in European countries: A multi-agent-based modelling approach
To reach climate neutrality goals, European countries need to reduce their transportation
sector emissions. To this end, implementing effective incentive policies to accelerate …
sector emissions. To this end, implementing effective incentive policies to accelerate …