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Ye Ren

Nanyang Technological University

19

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1484

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Empirical Mode Decomposition based ensemble deep learning for load demand time series forecasting

2017 Applied Soft Computing
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Random vector functional link network for short-term electricity load demand forecasting

2016 Information Sciences
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Review of Maximum Power Point Tracking Algorithm for Tidal Turbine Generator

2016
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A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting

2016 IEEE Transactions on Neural Networks
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Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]

2016 IEEE Computational Intelligence Magazine
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A Comparative Study of Empirical Mode Decomposition-Based Short-Term Wind Speed Forecasting Methods

2015 IEEE Transactions on Sustainable Energy
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Ensemble methods for wind and solar power forecasting—A state-of-the-art review

2015 Renewable & Sustainable Energy Reviews
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Modeling of steelmaking process with effective machine learning techniques

2015 Expert Systems With Applications
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Towards generating random forests via extremely randomized trees

2014 IJCNN | International Joint Conference on Neural Network
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A hybrid ARIMA-DENFIS method for wind speed forecasting

2013 FUZZ-IEEE | IEEE International Conference on Fuzzy Systems
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Citations (9)