Short-Term Load Forecasting Based on Pelican Optimization Algorithm and Dropout Long Short-Term Memories–Fully Convolutional Neural Network Optimization

Short-Term Load Forecasting Based on Pelican Optimization Algorithm and Dropout Long Short-Term Memories–Fully Convolutional Neural Network Optimization

In order to improve the prediction accuracy of short-term power loads in a power system, this paper proposes a short-term load prediction method (POA-DLSTMs-FCN) based on a combination of multi-layer lost long short-term memory (DLSTM) neural networks, fully convolutional neural networks (FCNs) and...

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Bibliographic Details
Main Authors: Haonan Wang, Shan Huang, Yue Yin, Tingyun Gu
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Energies
Subjects:
short-term load forecasting
pelican optimization algorithm
LSTM
FCN
Online Access:https://www.mdpi.com/1996-1073/17/23/6115
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