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A state-of-the-art review of artificial intelligence techniques for short-term electric load forecasting
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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The Nature of Statistical Learning Theory
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АДАПТИВНОЕ КРАТКОСРОЧНОЕ ПРОГНОЗИРОВАНИЕ ПОТРЕБЛЕНИЯ ЭЛЕКТРОЭНЕРГИИ АВТОНОМНЫМИ ЭНЕРГОСИСТЕМАМИ МАЛЫХ СЕВЕРНЫХ ПОСЕЛЕНИЙ НА ОСНОВЕ МЕТОДОВ РЕТРОСПЕКТИВНОГО РЕГРЕССИОННОГО АНАЛИЗА (В ПЕЧАТИ)
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Automatic Generation of a Type-2 Fuzzy System for Time Series Forecast based on Genetic Programming
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The Estimation of the Influence of Household Appliances on the Power Quality in a Microgrid System
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Cyber Attacks in Cyber-Physical Microgrid Systems: A Comprehensive Review
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Short-Term Electricity Demand Forecasting: A Comparative Evaluation of Models Based on Performance Criteria and Future Research Directions
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Automatic Generation of a Type-2 Fuzzy System for Time Series Forecast based on Genetic Programming
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Technology, Science and Culture – A Global Vision, Volume V
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Textual Data for Advanced Modelling of Electricity Demand and Price Dynamics
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