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Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
[HTML][HTML] Energy and sustainable development in smart cities: An overview
Smart cities are an innovative concept for managing metropolitan areas to increase their
residents' sustainability and quality of life. This article examines the management and …
residents' sustainability and quality of life. This article examines the management and …
[HTML][HTML] The Russia-Ukraine conflict: Its implications for the global food supply chains
Food is one of the most traded goods, and the conflict in Ukraine, one of the European
breadbaskets, has triggered a significant additional disruption in the global food supply …
breadbaskets, has triggered a significant additional disruption in the global food supply …
SPOSDS: A smart Polycystic Ovary Syndrome diagnostic system using machine learning
Abstract Polycystic Ovary Syndrome (PCOS) is a hormonal disorder that affects a large
percentage of women of reproductive age. PCOS causes imbalanced or delayed menstrual …
percentage of women of reproductive age. PCOS causes imbalanced or delayed menstrual …
Smart cities and urban energy planning: an advanced review of promises and challenges
This review explores the relationship between urban energy planning and smart city
evolution, addressing three primary questions: How has research on smart cities and urban …
evolution, addressing three primary questions: How has research on smart cities and urban …
[HTML][HTML] Self-healing in cyber–physical systems using machine learning: A critical analysis of theories and tools
The rapid advancement of networking, computing, sensing, and control systems has
introduced a wide range of cyber threats, including those from new devices deployed during …
introduced a wide range of cyber threats, including those from new devices deployed during …
Leveraging the power of machine learning and data balancing techniques to evaluate stability in smart grids
Modernizing traditional power grids into smart grids represents a significant advancement in
improving efficiency and sustainability within the energy sector. However, integrating …
improving efficiency and sustainability within the energy sector. However, integrating …
[HTML][HTML] An online reinforcement learning approach for HVAC control
Abstract Heating, Ventilation and Air Conditioning (HVAC) optimization for energy
consumption reduction is becoming ever more a topic of the utmost environmental and …
consumption reduction is becoming ever more a topic of the utmost environmental and …
A smart gas sensor using machine learning algorithms: sensor types based on IED configurations, fabrication techniques, algorithmic approaches, challenges …
A Nasri, A Boujnah, A Boubaker… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Over the past decade, machine learning (ML) and artificial intelligence (AI) have attracted
great interest in research and various practical applications. Currently, smart, fast, and high …
great interest in research and various practical applications. Currently, smart, fast, and high …
Intelligent modeling and optimization of solar plant production integration in the smart grid using machine learning models
To address the rising energy demands in industrial and public sectors, integrating zero‐
carbon emission energy sources into the power grid is crucial. Smart grids, equipped with …
carbon emission energy sources into the power grid is crucial. Smart grids, equipped with …