A practical solution based on convolutional neural network for non-intrusive load monitoring
出版年份 2021 全文链接
标题
A practical solution based on convolutional neural network for non-intrusive load monitoring
作者
关键词
-
出版物
Journal of Ambient Intelligence and Humanized Computing
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2021-01-02
DOI
10.1007/s12652-020-02720-6
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Improving Residential Load Disaggregation for Sustainable Development of Energy via Principal Component Analysis
- (2020) Arash Moradzadeh et al. Sustainability
- Performance Evaluation of Two Machine Learning Techniques in Heating and Cooling Loads Forecasting of Residential Buildings
- (2020) Arash Moradzadeh et al. Applied Sciences-Basel
- Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms
- (2020) Arash Moradzadeh et al. Sustainability
- Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models
- (2019) Qi Liu et al. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- Forecasting heating and cooling loads of buildings: a comparative performance analysis
- (2019) Sanjiban Sekhar Roy et al. Journal of Ambient Intelligence and Humanized Computing
- Non-Intrusive Load Monitoring and Classification of Activities of Daily Living Using Residential Smart Meter Data
- (2019) Michael A. Devlin et al. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- A Convolutional Neural Network-Based Deep Learning Methodology for Recognition of Partial Discharge Patterns from High-Voltage Cables
- (2019) Xiaosheng Peng et al. IEEE TRANSACTIONS ON POWER DELIVERY
- Load Disaggregation Using One-Directional Convolutional Stacked Long Short-Term Memory Recurrent Neural Network
- (2019) Yang Thee Quek et al. IEEE Systems Journal
- Residential Load Disaggregation Considering State Transitions
- (2019) Sevda Zeinal-Kheiri et al. IEEE Transactions on Industrial Informatics
- A Practical Solution for Non-Intrusive Type II Load Monitoring Based on Deep Learning and Post-Processing
- (2019) Weicong Kong et al. IEEE Transactions on Smart Grid
- Transfer Learning for Non-Intrusive Load Monitoring
- (2019) Michele D'Incecco et al. IEEE Transactions on Smart Grid
- Nonintrusive Load Monitoring Algorithm Using Mixed-Integer Linear Programming
- (2018) Fernando Marcos Wittmann et al. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- A Robust Transform-Domain Deep Convolutional Network for Voltage Dip Classification
- (2018) Azam Bagheri et al. IEEE TRANSACTIONS ON POWER DELIVERY
- Non-Intrusive Load Disaggregation Using Graph Signal Processing
- (2018) Kanghang He et al. IEEE Transactions on Smart Grid
- Simultaneous Detection of Multiple Appliances from Smart-meter Measurements via Multi-Label Consistent Deep Dictionary Learning and Deep Transform Learning
- (2018) Vanika Singhal et al. IEEE Transactions on Smart Grid
- A Cloud-based On-line Disaggregation Algorithm for Home Appliance Loads
- (2018) Million Abayneh Mengistu et al. IEEE Transactions on Smart Grid
- Disaggregating Transform Learning for Non-Intrusive Load Monitoring
- (2018) Megha Gaur et al. IEEE Access
- A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults
- (2018) Te Han et al. KNOWLEDGE-BASED SYSTEMS
- Load Disaggregation Based on Aided Linear Integer Programming
- (2017) Md. Zulfiquar Ali Bhotto et al. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
- Toward Non-Intrusive Load Monitoring via Multi-Label Classification
- (2017) Seyed Mostafa Tabatabaei et al. IEEE Transactions on Smart Grid
- Incorporating Appliance Usage Patterns for Non-Intrusive Load Monitoring and Load Forecasting
- (2017) Shirantha Welikala et al. IEEE Transactions on Smart Grid
- Sparse Optimization for Automated Energy End Use Disaggregation
- (2016) Dario Piga et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
- (2016) Marios Anthimopoulos et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Image Super-Resolution Using Deep Convolutional Networks
- (2016) Chao Dong et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Residential Appliance Identification Based on Spectral Information of Low Frequency Smart Meter Measurements
- (2016) Chinthaka Dinesh et al. IEEE Transactions on Smart Grid
- Interpreting human activity from electrical consumption data using reconfigurable hardware and hidden Markov models
- (2016) F. J. Ferrández-Pastor et al. Journal of Ambient Intelligence and Humanized Computing
- Data Mining Techniques for Detecting Household Characteristics Based on Smart Meter Data
- (2015) Krzysztof Gajowniczek et al. Energies
- Home appliance load disaggregation using cepstrum-smoothing-based method
- (2015) Seongbae Kong et al. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- Nonintrusive Load Monitoring: A Temporal Multilabel Classification Approach
- (2015) Kaustav Basu et al. IEEE Transactions on Industrial Informatics
- PALDi: Online Load Disaggregation via Particle Filtering
- (2015) Dominik Egarter et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Integration of legacy appliances into home energy management systems
- (2015) Dominik Egarter et al. Journal of Ambient Intelligence and Humanized Computing
- An unsupervised training method for non-intrusive appliance load monitoring
- (2014) Oliver Parson et al. ARTIFICIAL INTELLIGENCE
- Revealing household characteristics from smart meter data
- (2014) Christian Beckel et al. ENERGY
- Disaggregation of home energy display data using probabilistic approach
- (2012) Michael Zeifman IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- Residential Appliances Identification and Monitoring by a Nonintrusive Method
- (2011) Zhenyu Wang et al. IEEE Transactions on Smart Grid
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