Research on AI Model Consensus and Data Preprocessing Algorithm Based on Deep Learning

Data processing and consensus play an important role in various fields, and LSTM-based AI models have the ability to process sequence data, understand context, and process long-term dependencies, so they have attracted much attention in data processing and consensus tasks. In this study, an AI model based on LSTM is used for data processing and consensus algorithm research. For processing and the global consensus of the sequential data, the employment of an LSTM model has the memory unit and gating mechanism, respectively. In addition, the established data preprocessing techniques are used to realize the data processing and the global consensus. It is concluded based on the experimental results that the accuracy of the proposed method for processing and the global consensus is between 95% to 99%. In terms of data processing and the global consensus, this LSTM-based AI model has shown a strong learning ability. The LSTM algorithm also demonstrates good performance in processing unbalanced datasets, and it is helpful to improve the recall rate of the positive samples by the LSTM-based combined model.