A Cloud-Integrated Virtual Framework for LSTM-Driven Solar Forecasting and Residential Energy Management

With the increasing dependence on renewable energy-particularly solar power-accurate forecasting and intelligent energy management, it has become essential for reducing grid dependency and optimizing energy usage. This paper presents an AI-powered renewable energy forecasting and scheduling system d...

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Vydané v:	IEEE access Ročník 13; s. 151055 - 151071
Hlavní autori:	Devanathan, B., Suyampulingam, A., Selvaraj, P., Karuppasamy, Ilango, Ilamparithi, T.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Algorithms Alternative energy sources appliance scheduling Decision trees Energy consumption Energy management Energy value Forecasting Greedy algorithms Home appliances home energy management system Household appliances Long short term memory Machine learning machine learning algorithms Meteorological data Optimization Predictive models priority-based greedy scheduling algorithm algorithms priority-based scheduling Random forests Real time Real-time systems Renewable energy Renewable resources Residential energy Schedules Scheduling Smart buildings Solar energy solar energy forecasting Solar power generation Support vector machines
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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