Multi-objective evolutionary algorithms applied to non-intrusive load monitoring-Reference-Cited by-同舟云学术

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Multi-objective evolutionary algorithms applied to non-intrusive load monitoring

Published:2019-12 Issue: Volume:177 Page:105961
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Li Ling,Yang Liyu,Chen Hao,Li Ming,Zhang Congxuan

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi Province

5511 Science and Technology Innovation Talent Project of Jiangxi Province

Advantage Subject Team Project of Jiangxi Province

Graduate Innovation Foundation of Jiangxi Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference43 articles.

1. Characteristics of residential energy consumption in China: findings from a household survey;Zheng;Energy Policy,2014

2. Nonintrusive load monitoring algorithm using mixed-integer linear programming;Wittmann;IEEE Trans. Consum. Electron.,2018

3. ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation;Amini;Electr. Power Syst. Res.,2016

4. A novel multi-time-scale modeling for electric power demand forecasting: from short-term to medium-term horizon;Boroojeni;Electr. Power Syst. Res.,2017

5. Assessing human activity in elderly people using non-intrusive load monitoring;Alcalá;Sensors,2017

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-indicator based multi-objective evolutionary algorithm with application to neural architecture search;International Journal of Machine Learning and Cybernetics;2024-08-27

2. A Siamese CNN + KNN-Based Classification Framework for Non-intrusive Load Monitoring;Journal of Control, Automation and Electrical Systems;2023-05-01

3. The research of innovation path of power monitoring and dispatching under the vision of carbon neutrality based on mobile edge computing;Soft Computing;2022-05-14

4. An advanced smart home energy management system considering identification of ADLs based on non-intrusive load monitoring;Electrical Engineering;2022-04-17

5. Selection of features from power theories to compose NILM datasets;Advanced Engineering Informatics;2022-04

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