Research on Photovoltaic Power Generation Prediction Based on CNN-BILSTM-Attention Modeling
A composite model combining convolutional neural network(CNN),bi-directional long and short-term memory network(BiLSTM)and attention mechanism(CNN-BiLSTM-Attention)is proposed CNN is utilized to extract the local features of the time series data,then the long-term dependencies in the data are captured by BiLSTM,and finally,the attention mechanism is introduced to enhance the model's attention to the important information.Through experiments on real datasets,the advantages of the proposed model over traditional time series prediction methods and a single deep learning model in terms of prediction accuracy and stability are verified.
time series forecastingdeep learningconvolutional neural network(CNN)bidirectional long short-term memory network(BiLSTM)attention mechanism
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