… approach for wind power prediction. The characteristics of NWP and historical wind power
data are extracted by using the feature extraction technique, the predictor is designed based …

… This paper proposes a feature extraction scheme based on convolutional neural networks
… for wind power prediction. The experimental results show that the proposed feature extractor …

… end-to-end environmental features extraction model (EFEM) … prediction unit, and VGGNet
is used as an EFs extraction unit … models fixed by default features, the linear regression model …

… When a trial is input to both pNNs features are obtained by continually calculating the power
… through a feature extraction (FE) window. These calculations reduce predictions within the …

… long-term PV power prediction can provide reference for … PV power prediction is widely
used to make day-ahead power generation plan [13], and ultra-shortterm PV power prediction …

… wind power prediction model based on double feature extraction … map model, a dual feature
selection module, a quadratic … multi-step prediction module. The details are shown in Fig. 6. …

… This section will present the results of wind power prediction, and three latest deep
learning prediction models (eg, CNN model, LSTM model, GRU model) and five popular …

… with the high integration of wind power into the electricity market. This … feature extraction,
deep learning algorithm and error correction strategy for multi-step wind speed prediction. The …

… power law non-linearity in speech spectrum estimation by compressing/expanding power
spectrum in autocorrelation-based linear prediction… to obtain spectral features that present less …

… the extracted features with the predicting power, a Pearson correlation analysis method is
used in this paper [43,44]. The extracted feature data with high impact on power prediction are …