<ul><li>This paper utilizes machine learning algorithms to forecast and analyze financial time series.</li><li>It employs a denoising autoencoder to filter out random noise fluctuations from the main contract price data.</li><li>The filtered data is then processed using one-dimensional convolution to extract key information.</li><li>A GANs network is utilized to further analyze the filtered and dimensionality-reduced price data for predicting significant price changes in real-time.</li></ul>

Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms

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