Temporal Fusion Transformer with Non-Intrusive Attention for Data-Driven Electricity Load Forecasting-Reference-Cited by-同舟云学术

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Temporal Fusion Transformer with Non-Intrusive Attention for Data-Driven Electricity Load Forecasting

Published:2023-12-22 Issue: Volume: Page:275-281
ISSN:
Container-title:2023 7th International Conference on Power and Energy Engineering (ICPEE)
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Author:

Cui Dongmei¹,Xiang Weishan²,Zang Zhibin³,Yu Hai⁴,Ou Zhujian⁵,Mao Yanfang⁵,He Zhimin⁴

Affiliation:

1. State Grid Information & Telecommunication Co., Ltd,Artificial intelligence technology research and development center,Beijing,China

2. Xiamen Yilijiao Information Technology Co., Ltd,GIS Platform Business Unit,Xiamen,China

3. Xiamen Yilijiao Information Technology Co., Ltd,Xiamen,China

4. Digital Technology Research Institute, State Grid Smart Grid Research Institute Co., LTD,Nanjing,China

5. State Grid Nantong Power Supply Company,Development and planning department,Nantong,Jiangsu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10453650/10453664/10453838.pdf?arnumber=10453838

Reference24 articles.

1. The Time Series Approach to Short Term Load Forecasting

2. Time series forecasting using a hybrid ARIMA and neural network model

3. Short term load forecastiong using time seasonal autoregressive integrated moving average[J];Razak;Penerbit Utm,2007

4. Medium and Long-term Load Forecasting Based on Census X12-SARIMA Model;Zhan-Jun,2014

5. Electric Load Forecasting Based on Statistical Robust Methods

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