Advancing ensemble learning techniques for residential building electricity consumption forecasting: Insight from explainable artificial intelligence
Jihoon Moon,
Muazzam Maqsood,
Dayeong So
et al.
Abstract:Accurate electricity consumption forecasting in residential buildings has a direct impact on energy efficiency and cost management, making it a critical component of sustainable energy practices. Decision tree-based ensemble learning techniques are particularly effective for this task due to their ability to process complex datasets with high accuracy. Furthermore, incorporating explainable artificial intelligence into these predictions provides clarity and interpretability, allowing energy managers and homeow… Show more
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