Retraction
Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique
Paper Information
Record ID:
62765
Author(s):
Journal:
Publication Date:
January 27, 2020
Retraction Date:
August 13, 2024
(1.3 year years ago)
Subjects:
Institutions:
Country:
🇮🇳 IndiaArticle Type:
Publisher:
Springer - Nature Publishing Group
Open Access:
Yes
PubMed ID:
Not indexed in PubMed
Retraction PubMed ID:
Not indexed in PubMed
Retraction Details
Citations (65)
65
Total Citations7
Post-Retraction(10.8%)
58
Pre-Retraction0
Same DayPost-Retraction Citation Analysis
1
Within 30 days
7
Within 1 year
0
After 2+ years
336
Days since retraction (latest)
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Short-term wind power forecasting with an intermittency-trait-driven methodology
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A deep-learning wind speed interval forecasting architecture based on modified scaling approach with feature ranking and two-output gated recurrent unit
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727 days before retraction
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820 days before retraction
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51 citations
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865 days before retraction
Wind power prediction based on EEMD-Tent-SSA-LS-SVM
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946 days before retraction
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A novel hybrid model based on ESMD-PE and mRMR-LSTM-Adaboost for short-term wind power prediction
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3 citations
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986 days before retraction
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995 days before retraction
An Intelligent Evaluation Method of Information Course Teaching Effect Based on Image Analysis
Haidong Chen, JuFang Zhang
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1 citation
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1009 days before retraction
A multi-location short-term wind speed prediction model based on spatiotemporal joint learning
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1019 days before retraction
Secondary factor induced wind speed time-series prediction using self-adaptive interval type-2 fuzzy sets with error correction
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17 citations
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1021 days before retraction
Quick Stats
Total Citations:
65
Years Since Retraction:
1.3 year
Open Access:
Yes
Last Checked:
Jul 24, 2025