AYRNA Research Group
LEARNING AND ARTIFICIAL NEURAL NETWORKS

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Applications - Renewable Energy

Description

  

Publications

  • Fuzzy-based ensemble methodology for accurate long-term prediction and interpretation of extreme significant wave height events
  • Simultaneous short-term significant wave height and energy flux prediction using zonal multi-task evolutionary artificial neural networks
  • Building Suitable Datasets for Soft Computing and Machine Learning Techniques from Meteorological Data Integration: A Case Study for Predicting Significant Wave Height and Energy Flux
  • Short- and long-term energy flux prediction using Multi-Task Evolutionary Artificial Neural Networks
  • Robust estimation of wind power ramp events with reservoir computing
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