Correction: Short-time photovoltaic output prediction method based on depthwise separable convolution Visual Geometry group- deep gate recurrent neural network
Year: 2025
Type: erratum
Abstract: Correction on: To overcome these challenges, this paper utilizes the Exponential Linear Units (ELU) activation function, introduced by Clevert et al., in 2016. ELU maintains nonlinearity while providing a better handling of negative inputs, avoiding the "dying ReLU" problem (Staer-Jensen et al., 2018). This characteristic has made ELU popular in deep neural networks, particularly in natural language processing and image processing, where it has achieved notable results. The reference for [Staer-Jensen et al., 2018] was erroneously written as [Staer-Jensen, H., Sunde, K., Nakstad, E. R., Eritsland, J., and Andersen, G. Ø . (2018). Comparison of Three Haemodynamic Monitoring Methods in Comatose Post Cardiac Arrest Patients. Scand. Cardiovasc. J. 52 (3), 141–148. doi:10.1080/14017431.2018.1450992]. It should be [Clevert, D.-A., Untertiner, T., and Hochreiter, S. (2016). Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). arXiv preprint. arXiv: 1511.07289, 4.5, 11].
Source: Frontiers in Energy Research
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,077
OpenAlex ID: W4415507083
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