WiMi Hologram Cloud develops LSTM-based data analysis system

WiMi Hologram Cloud announced an LSTM-based data analysis system to provide clients with cutting-edge tools to trade in the complex cryptocurrency environment. As a decentralized digital currency, the price of Bitcoin is affected by a variety of factors, such as market demands, policy regulations, and technological innovations. Therefore, the prediction of price trends needs to comprehensively consider these factors and find patterns from a large amount of data. Traditional data analysis methods make it difficult to handle such complex data, but the LSTM algorithm can solve this problem. WiMi uses the LSTM algorithm to predict cryptocurrency prices, which allows it to more accurately predict the price of Bitcoin. The LSTM algorithm is a recurrent neural network. The system uses a variety of data sources, including historical prices, transaction volumes, social media data, and more. The system uses the LSTM algorithm to analyze these data and generate predictions of bitcoin price trends. LSTM is a special type of RNN architecture that can efficiently handle time-series-dependent data. It avoids the problem of gradient vanishing or gradient explosion when dealing with long-term dependencies by introducing a “gate” structure to control the flow of information. This makes LSTM widely used in the fields of speech recognition, natural language processing, and time series analysis.