PUBLISHED PAPERS #02.03
| Vagif Gasimov, Maryam Asadova. Methods of Artificial Intelligence and Machine Learning Forecasting and Optimization of Energy Consumption in Smart Cities |
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| Abstract. Smart cities are transforming urban life through advanced technologies, and efficient energy management is one of the key challenges they face. The rapid increase in energy consumption requires innovative approaches to optimize energy supply and demand. This article explores the application of artificial intelligence (AI) and machine learning (ML) algorithms for energy supply management in smart cities. It examines how these technologies can forecast energy consumption, balance supply and demand, and optimize energy management through real-time adjustments. The paper also highlights mathematical models and international case studies to illustrate the potential of AI and ML in achieving energy efficiency and sustainability. The findings demonstrate the effectiveness of these technologies in improving energy management and offer insights into future advancements in the field. |
| Keywords: smart cities, energy management, artificial intelligence, machine learning, energy forecasting, supply-demand optimization |
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| DOI: https://doi.org/10.30546/MaCoSEP2025.1037 |