Correction: Grey wolf optimization–based deep echo state network for time series prediction

[Be that as it may, the execution of the GWODESN is superior than that of the conventional ESN.] A correction has been made to the section [4 Experimental setup, results, and discussion,4.3 Mackey-Glass System]: "[Be that as it may, the performance of the GWODESN is superior to that of the conventional ESN]"[Figure 10 appears that the GWODESN show has superior forecast precision and soundness than other models.] A correction has been made to the section [4 Experimental setup, results, and discussion,4.3 Mackey-Glass System]: "[Figure 10 shows that the GWODESN has superior forecast precision and soundness to other models.]" [Comparative test that comes about on four time-series forecast assignments clearly illustrates that the proposed GWODESN outflank the ELM, LSTM, and ESN benchmarks] [Within the future, we will center on progressing the network topology and apply the model in other domains, such as wind energy prediction.] A correction has been made to the section [5 CONCLUSION]: "[In the future, we will center on improving the network topology of the GWODESN and apply the model in other domains, such as wind energy prediction and photovoltaic power forecasting.]"

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Publication Details

Journal
Frontiers in Energy Research
Published
2026-03-09
DOI
https://doi.org/10.3389/fenrg.2026.1770773
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Correction: Grey wolf optimization–based deep echo state network for time series prediction

Haiyang Zhang, Xiaojuan Chen
Frontiers in Energy Research
Neural Networks and Reservoir Computing
article

Correction: Grey wolf optimization–based deep echo state network for time series prediction

Haiyang Zhang, Xiaojuan Chen
article en

Abstract

[Be that as it may, the execution of the GWODESN is superior than that of the conventional ESN.] A correction has been made to the section [4 Experimental setup, results, and discussion,4.3 Mackey-Glass System]: "[Be that as it may, the performance of the GWODESN is superior to that of the conventional ESN]"[Figure 10 appears that the GWODESN show has superior forecast precision and soundness than other models.] A correction has been made to the section [4 Experimental setup, results, and discussion,4.3 Mackey-Glass System]: "[Figure 10 shows that the GWODESN has superior forecast precision and soundness to other models.]" [Comparative test that comes about on four time-series forecast assignments clearly illustrates that the proposed GWODESN outflank the ELM, LSTM, and ESN benchmarks] [Within the future, we will center on progressing the network topology and apply the model in other domains, such as wind energy prediction.] A correction has been made to the section [5 CONCLUSION]: "[In the future, we will center on improving the network topology of the GWODESN and apply the model in other domains, such as wind energy prediction and photovoltaic power forecasting.]"

Frontiers in Energy ResearchVol. 14
Changchun University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 33%
Neural Networks and Reservoir Computing
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