FBiLSTM-Attention short-term load forecasting based on fuzzy logic

FBiLSTM-Attention short-term load forecasting based on fuzzy logic

Aiming at the problem of high uncertainty in power load data due to various factors, a fuzzy logic based FBiLSTM Attention short-term load forecasting model was proposed by combining the uncertainty of load data with deep learning algorithms to improve the accuracy of load forecasting. Firstly, the...

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Bibliographic Details
Main Authors: Yan ZHANG, Zepeng KANG, Xiaozhi GAO, Nan YANG, Zhaolei WANG
Format: Article
Language:zho
Published: Hebei University of Science and Technology 2025-02-01
Series:Journal of Hebei University of Science and Technology
Subjects:
data processing; fuzzy logic; load forecasting; bi-directional long short-term memory(bilstm); attention mechanism(attention)
Online Access:https://xuebao.hebust.edu.cn/hbkjdx/article/pdf/b202501005?st=article_issue
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https://xuebao.hebust.edu.cn/hbkjdx/article/pdf/b202501005?st=article_issue

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