LSTM-Based Reinforcement Q Learning Model for Non Intrusive Load Monitoring

Kalthoum Zaouali; Mohamed Lassaad Ammari; Ridha Bouallègue

doi:10.1007/978-3-030-99619-2_1

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LSTM-Based Reinforcement Q Learning Model for Non Intrusive Load Monitoring

Kalthoum Zaouali Mohamed Lassaad Ammari Ridha Bouallègue

Year: 2022 Lecture notes in networks and systems Pages: 1-13 Publisher: Springer International Publishing

DOI: 10.1007/978-3-030-99619-2_1

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Keywords:

Reinforcement learning Computer science Smart meter Energy (signal processing) Artificial intelligence Machine learning Long short term memory Scale (ratio) Deep learning Smart grid Real-time computing Data mining Engineering Recurrent neural network Artificial neural network Statistics

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Smart Grid Energy Management

Physical Sciences → Engineering → Electrical and Electronic Engineering

Smart Parking Systems Research

Physical Sciences → Engineering → Building and Construction

Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

LSTM-Based Reinforcement Q Learning Model for Non Intrusive Load Monitoring

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