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Title	Enhancing Energy Efficiency In Smart Cities Through Neural Support Vector Machine Learning For Smart Grids
ID_Doc	23799
Authors	Indra G.; Gopi T.; Gangwar P.K.; Senthil Kumar K.R.; Rajendiran M.; Balasubramani S.
Year	2025
Published	Communications in Computer and Information Science, 1971 CCIS
DOI	http://dx.doi.org/10.1007/978-3-031-85666-2_3
Abstract	Long-term sustainability is increasingly important for smart cities, and the energy management in smart cities plays a key role in achieving the aim of research. This research focuses on improving energy efficiency using Neural Support Vector Machine (NSVM) learning in smart cities to measure the energy consumption to optimize smart grids. The research highlights the limitations of smart grid to integrate renewable energy sources and energy consumption patterns. This paper uses advanced model to analyze, forecast, and improve energy consumption in smart grids. The proposed NSVM-based machine learning understands the data energy usage patterns with improved accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Author Keywords	Energy Efficiency; Neural Support Vector Machine; Smart Cities; Smart Grids

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