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Yu-Hsiu Lin

Researcher at National Taipei University of Technology

Publications -  36
Citations -  1022

Yu-Hsiu Lin is an academic researcher from National Taipei University of Technology. The author has contributed to research in topics: Smart grid & Demand response. The author has an hindex of 13, co-authored 33 publications receiving 768 citations. Previous affiliations of Yu-Hsiu Lin include Southern Taiwan University of Science and Technology & Providence College.

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Journal ArticleDOI

An Advanced Home Energy Management System Facilitated by Nonintrusive Load Monitoring With Automated Multiobjective Power Scheduling

TL;DR: The experimental results reveal that the proposed advanced HEMS facilitated by a nonintrusive load monitoring (NILM) technique with an automated nondominated sorting genetic algorithm-II (NSGA-II)-based multiobjective in-home power scheduling mechanism is workable and feasible.
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Development of an Improved Time–Frequency Analysis-Based Nonintrusive Load Monitor for Load Demand Identification

TL;DR: The improved NILM proposed in this paper incorporates a multiresolution S-transform-based transient feature extraction scheme with a modified 0-1 multidimensional knapsack algorithm-based load identification method to identify individual household appliances that may either be energized simultaneously or be identified under similar real power consumption.
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Modern development of an Adaptive Non-Intrusive Appliance Load Monitoring system in electricity energy conservation

TL;DR: In this paper, a novel Adaptive Non-Intrusive Appliance Load Monitoring (ANIALM) system that integrates appliance energizing and de-energizing transient feature extraction methods with soft-computing techniques is developed to keep track of the energy consumption of each appliance.
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Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes

TL;DR: This work designs and implements a smart edge analytics-empowered power meter prototype considering advanced AI in DSM for smart homes, designed and implemented as edge analytics in the architecture described and developed toward a next-generation smart sensing infrastructure forsmart homes.
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Non-Intrusive Load Monitoring by Novel Neuro-Fuzzy Classification Considering Uncertainties

TL;DR: An NILM system with a novel hybrid classification technique that integrates Fuzzy C-Means clustering-piloting Particle Swarm Optimization with Neuro-Fuzzy Classification considering uncertainties is proposed and is feasible.