A Novel Method Combining Grayscale Images and Convolutional Neural Networks for Non-Intrusive Load Identifications-Reference-Cited by-同舟云学术

A Novel Method Combining Grayscale Images and Convolutional Neural Networks for Non-Intrusive Load Identifications

Published:2022-11-03 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Fuzzy Theory and Its Applications (iFUZZY)
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Author:

Tsai Men-Shen¹,Li Yuan-Hao²,Lin Yen-Kuang³

Affiliation:

1. Graduate Institute of Automation Tech. Research Center of Energy Conservation for New Generation of Residential, Commercial, and Industrial Sectors National Taipei University of Tech.,Taipei,Taiwan

2. Graduate Institute of Automation Tech. National Taipei University of Tech.,Taipei,Taiwan

3. College of Mechanical & Electrical Engineering National Taipei University of Tech.,Taipei,Taiwan

Funder

Ministry of Science and Technology

Ministry of Education (MOE) in Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9985216/9985217/09985221.pdf?arnumber=9985221

Reference10 articles.

1. High accuracy event detection for Non-Intrusive Load Monitoring

2. A Factorial Hidden Markov Model for Energy Disaggregation based on Human Behavior Analysis

3. Frequency Invariant Transformation of Periodic Signals (FIT-PS) for Classification in NILM

4. A hidden Markov model based procedure for identifying household electric loads

5. Non Intrusive Load Monitoring and Load Disaggregation using Transient Data Analysis

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