Short-term LOAD Forecasting Method of TPA-LSTNet Model Based on Time Series Clustering-Reference-Cited by-同舟云学术

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Short-term LOAD Forecasting Method of TPA-LSTNet Model Based on Time Series Clustering

Published:2022-09-28 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Renewable Energy and Power Engineering (REPE)
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Author:

Li Zhuyun¹,Hu Chunchao¹,Zhang Yanxu¹,Liang Guobang¹,Huang Zhuolin¹,Zhang Qiran¹

Affiliation:

1. China Southern Power Grid Technology Co.,Ltd.,Guangdong Provincial Key Laboratory of New Technology for Smart Grid,Guangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9948700/9948714/09949388.pdf?arnumber=9949388

Reference23 articles.

1. Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network;sherstinsky;Physica D Nonlinear Phenomena,2020

2. Learning long-term dependencies with gradient descent is difficult [J];y;IEEE Transactions on Neural Networks,1994

3. Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks

4. Energy Load Forecasting using Deep Learning Approach-LSTM and GRU in Spark Cluster

5. Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Cited by 1 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. TCN-LSTNet with Sliding Time Window Featured Short-Term Load Forecasting for Integrated Energy System;2023 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia);2023-07-07

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