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CORRECTION article

Front. Energy Res.
Sec. Solar Energy
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1548438
This article is part of the Research Topic Ensuring the Reliability of Solar Photovoltaics View all 8 articles

Expression of Concern: Short-time Photovoltaic output prediction method based on Depthwise Separable Convolution Visual Geometry Group-Deep Gate Recurrent Neural Network

Provisionally accepted
Frontiers Editorial Office Frontiers Editorial Office *
  • Frontiers Media SA, Lausanne, Switzerland

This article is a correction to:

  1. Short-time photovoltaic output prediction method based on depthwise separable convolution Visual Geometry group- deep gate recurrent neural network

    1. Read original article

The final, formatted version of the article will be published soon.

    Expression of Concern: Short-time Photovoltaic output prediction method based on Depthwise Separable Convolution Visual Geometry Group-Deep Gate Recurrent Neural Network An expression of concern on Zhang L, Zhao S, Zhao G, Wang L, Liu B, Na Z, Liu Z, Yu Z and He W (2024) Short-time photovoltaic output prediction method based on depthwise separable convolution Visual Geometry group- deep gate recurrent neural network. Front. Energy Res. 12:1447116. doi: 10.3389/fenrg.2024.1447116 With this notice, Frontiers states its awareness of concerns regarding the content of the article “Short-time Photovoltaic output prediction method based on Depthwise Separable Convolution Visual Geometry Group-Deep Gate Recurrent Neural Network” published on 1st August 2024. Our Research Integrity team will conduct an investigation in full accordance with our procedures. The situation will be updated as soon as the investigation is complete.

    Keywords: Photovoltaic power output prediction, deep learning, Depthwise separable convolution, VGG, Gate Recurrent Neural Network

    Received: 19 Dec 2024; Accepted: 19 Dec 2024.

    Copyright: © 2024 Editorial Office. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Frontiers Editorial Office, Frontiers Media SA, Lausanne, Switzerland

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