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Deep Neural Network Based Demand Side Short Term Load Forecasting

Energies (Basel), 2017-01, Vol.10 (1), p.3-3

2017

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Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles

IEEE access, 2019, Vol.7, p.75143-75152

2019

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Denoising Autoencoder-Based Missing Value Imputation for Smart Meters

IEEE access, 2020, Vol.8, p.40656-40666

2020

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Quantile Autoencoder With Abnormality Accumulation for Anomaly Detection of Multivariate Sensor Data

IEEE access, 2022, Vol.10, p.70428-70439

2022

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Data-Driven Baseline Estimation of Residential Buildings for Demand Response

Energies (Basel), 2015-09, Vol.8 (9), p.10239-10259

2015

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Development of deep autoencoder-based anomaly detection system for HANARO

Nuclear Engineering and Technology, 2023, 55(2), , pp.475-483

2023

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Quantile-Mixer: A Novel Deep Learning Approach for Probabilistic Short-term Load Forecasting

IEEE transactions on smart grid, 2024-03, Vol.15 (2), p.1-1

2024

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Gaussian Residual Bidding Based Coalition for Two-Settlement Renewable Energy Market

IEEE access, 2018-01, Vol.6, p.43029-43038

2018

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Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis

IEEE transactions on power systems, 2020-03, Vol.35 (2), p.1048-1060

2020

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Development of a Checklist for Predicting Suicidality Based on Risk and Protective Factors: The Gwangju Checklist for Evaluation of Suicidality

PSYCHIATRY INVESTIGATION, 2022, 19(6), , pp.470-479

2022

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Coalition-based bidding strategies for integrating renewable energy sources in electricity market

2017 IEEE Power & Energy Society General Meeting, 2017, p.1-5

2017

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Can Untrained Neural Networks Detect Anomalies?

IEEE transactions on industrial informatics, 2024-04, Vol.20 (4), p.6477-6488

2024

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Deep neural network based demand side short term load forecasting

2016 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2016, p.308-313

2016

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An approach to constructing effective training data for a classification model to evaluate the reliability of a passive safety system

Reliability engineering & system safety, 2022-06, Vol.222, p.108446, Article 108446

2022

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Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code

Expert systems with applications, 2022-08, Vol.200, p.116966, Article 116966

2022

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Robust Operation of Energy Storage System with Uncertain Load Profiles

Energies (Basel), 2017-03, Vol.10 (4), p.416

2017

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Development of deep autoencoder-based anomaly detection system for HANARO

Nuclear engineering and technology, 2023, Vol.55 (2), p.475-483

2023

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Development of a Checklist for Predicting Suicidality Based on Risk and Protective Factors: The Gwangju Checklist for Evaluation of Suicidality

Psychiatry investigation, 2022-06, Vol.19 (6), p.470-479

2022

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A framework for baseline load estimation in demand response: Data mining approach

2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2014, p.638-643

2014

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Short-Term Load Forecasting based on ResNet and LSTM

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018, p.1-6

2018

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Residential Load Profile Clustering via Deep Convolutional Autoencoder

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018, p.1-6

2018

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Early Intervention Model for Mental Health in Korean Youth: Mindlink

Korean Journal of Schizophrenia Research, 2022-04, Vol.25 (1), p.1-9

2022

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Customer Load Pattern Analysis using Clustering Techniques

KEPCO Journal on Electric Power and Energy, 2016-03, Vol.2 (1), p.61-69

2016

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Deep Neural Network Based Demand Side Short Term Load Forecasting

Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles

Denoising Autoencoder-Based Missing Value Imputation for Smart Meters

Quantile Autoencoder With Abnormality Accumulation for Anomaly Detection of Multivariate Sensor Data

Data-Driven Baseline Estimation of Residential Buildings for Demand Response

Development of deep autoencoder-based anomaly detection system for HANARO

Quantile-Mixer: A Novel Deep Learning Approach for Probabilistic Short-term Load Forecasting

Gaussian Residual Bidding Based Coalition for Two-Settlement Renewable Energy Market

Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis

Development of a Checklist for Predicting Suicidality Based on Risk and Protective Factors: The Gwangju Checklist for Evaluation of Suicidality

Coalition-based bidding strategies for integrating renewable energy sources in electricity market

Can Untrained Neural Networks Detect Anomalies?

Deep neural network based demand side short term load forecasting

An approach to constructing effective training data for a classification model to evaluate the reliability of a passive safety system

Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code

Robust Operation of Energy Storage System with Uncertain Load Profiles

Development of deep autoencoder-based anomaly detection system for HANARO

Development of a Checklist for Predicting Suicidality Based on Risk and Protective Factors: The Gwangju Checklist for Evaluation of Suicidality

A framework for baseline load estimation in demand response: Data mining approach

Short-Term Load Forecasting based on ResNet and LSTM

Residential Load Profile Clustering via Deep Convolutional Autoencoder

Early Intervention Model for Mental Health in Korean Youth: Mindlink

Customer Load Pattern Analysis using Clustering Techniques

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