AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Y Himeur, M Elnour, F Fadli, N Meskin, I Petri… - Artificial Intelligence …, 2023 - Springer
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

[HTML][HTML] Energetics Systems and artificial intelligence: Applications of industry 4.0

T Ahmad, H Zhu, D Zhang, R Tariq, A Bassam, F Ullah… - Energy Reports, 2022 - Elsevier
Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …

Machine learning and deep learning in energy systems: A review

MM Forootan, I Larki, R Zahedi, A Ahmadi - Sustainability, 2022 - mdpi.com
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 …

Artificial Intelligence and emerging digital technologies in the energy sector

W Lyu, J Liu - Applied energy, 2021 - Elsevier
Digitalization is an increasingly important direction of energy innovation moving forward.
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

I Palomares, E Martínez-Cámara, R Montes… - Applied …, 2021 - Springer
Abstract The17 Sustainable Development Goals (SDGs) established by the United Nations
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …

[HTML][HTML] Renewable energy and sustainable agriculture: Review of indicators

A Bathaei, D Štreimikienė - Sustainability, 2023 - mdpi.com
Sustainable agriculture strives to ensure future food and energy supply while safeguarding
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

D Liu, S Zhong, L Lin, M Zhao, X Fu, X Liu - Advanced Engineering …, 2022 - Elsevier
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 …

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 …

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 …

Exploratory policy analysis for electric vehicle adoption in European countries: A multi-agent-based modelling approach

N Neshat, M Kaya, SG Zare - Journal of Cleaner Production, 2023 - Elsevier
To reach climate neutrality goals, European countries need to reduce their transportation
sector emissions. To this end, implementing effective incentive policies to accelerate …