Abstract: The goal of that paper is to show a possibility for the disaggregation of electrical appliances in the power profile of residential buildings.
The goal of that paper is to show a possibility for the disaggregation of electrical appliances in the power profile of residential buildings.
The goal of that paper is to show a possibility for the disaggregation of electrical appliances in the power profile of residential buildings.
Smart meter systems detection & classification using artificial neural networks ... networks; Manuals; Monitoring; Refrigerators; Switches; Weight measurement.
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This paper builds a power consumption prediction model based on artificial neural networks, aiming at achieving accurate demand forecasting in the smart ...
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Furthermore, Smart meters offer numerous opportunities in electricity load analysis such as load prediction with high accuracy, intelligent management, and the ...
The aim of this work is to a carry-out Comprehensive Review of Artificial Neural Network Techniques Used for Smart Meter-Embedded forecasting System.
Two efficient deep neural networks, LSTM and CNN, are respectively applied to predict the presence. (injection) of malfunction in the smart meters inside a ...
Some applications of data mining approaches related to smart meter data are graph signal processing clustering and convolution neural network (CNN) ...
Oct 26, 2023 · This article proposes a deep learning (DL) model made of Long Short Term Memory (LSTM) and Adaptive Neuro Fuzzy Inference System (ANFIS) to detect fault in ...