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Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Non-Intrusive Load Monitoring (NILM) is a valuable technique for breaking down overall power consumption into the energy usage of individual...
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Thresholding methods in non-intrusive load monitoring
Non-intrusive load monitoring (NILM) is the problem of predicting the status or consumption of individual domestic appliances only from the knowledge...
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Graph-Based Dependency-Aware Non-Intrusive Load Monitoring
Non-intrusive load monitoring (NILM) is able to analyze and predict users’ power consumption behaviors for further improving the power consumption...
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Non-intrusive load monitoring techniques for the disaggregation of ON/OFF appliances
Nowadays, Non-Intrusive Load Monitoring techniques are sufficiently accurate to provide valuable insights to the end-users and improve their...
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Multi-agent Reinforcement Learning Based User-Centric Demand Response with Non-intrusive Load Monitoring
This research proposes a multi-agent reinforcement learning framework as a home energy management algorithm that focuses on user needs and...
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Pre-trained non-intrusive load monitoring model for recognizing activity of daily living
Non-intrusive load monitoring (NILM) is a technology that analyzes total electricity consumption data to determine whether a specific type of...
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Non-intrusive load monitoring based on semi-supervised smooth teacher graph learning with voltage–current trajectory
Non-intrusive load monitoring (NILM) is a novel and cost-effective technology for monitoring load electricity energy consumption detail. It can...
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Smart Energy Management System Using Non-intrusive Load Monitoring
Energy Management is a problem faced by many around the world. The ever-rising demand for energy is putting a strain on the worldwide resources....
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A multi-task learning model for non-intrusive load monitoring based on discrete wavelet transform
Non-intrusive load monitoring (NILM) is an algorithm that can help to present the power consumption of each domestic appliance by analyzing the total...
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Non-intrusive load monitoring method with inception structured CNN
Non-intrusive load monitoring (NILM) is an important part of smart grid, which can recognize home electrical appliances. Compared to traditional...
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Non-intrusive load monitoring algorithm based on household electricity use habits
The construction of smart grid is an important part of improving the utilization rate of electric energy. As an important way for the construction of...
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Research on Non-intrusive Household Load Identification Method Applying LightGBM
With the continuous advancement of intelligence and big data technology, efficient and accurate non-intrusive load identification is of great...
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Non intrusive load monitoring for demand side management
In the context of a pilot project, the Lugaggia Innovation Community (LIC), we address the problem of non-intrusive load monitoring for the purpose...
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Investigating the performance gap between testing on real and denoised aggregates in non-intrusive load monitoring
Prudent and meaningful performance evaluation of algorithms is essential for the progression of any research field. In the field of Non-Intrusive...
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A feature fusion technique for improved non-intrusive load monitoring
Load identification is an essential step in Non-Intrusive Load Monitoring (NILM), a process of estimating the power consumption of individual...
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NDFuzz: a non-intrusive coverage-guided fuzzing framework for virtualized network devices
Network function virtualization provides programmable in-network middlewares by leveraging virtualization technologies and commodity hardware and has...
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Deep Learning Based Solution for Appliance Operational State Detection and Power Estimation in Non-intrusive Load Monitoring
This paper introduces a novel NILM algorithm that utilizes deep learning Temporal Convolutional Networks (TCN) for the regression and classification...
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A Multi-label Time Series Classification Approach for Non-intrusive Water End-Use Monitoring
Numerous real-world problems from a diverse set of application areas exist that exhibit temporal dependencies. We focus on a specific type of time...
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Application of improved DBN and GRU based on intelligent optimization algorithm in power load identification and prediction
Non intrusive load monitoring belongs to the key technologies of intelligent power management systems, playing a crucial role in smart grids. To...
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On the non-intrusive extraction of residents’ privacy- and security-sensitive information from energy smart meters
Energy smart meters have become very popular in monitoring and smart energy management applications. However, the acquired measurements except the...
