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With the rapid development of computer technology, people's demand for information processing continues to increase. In terms of howto better store and manage data with modern computing methods, scholars have begun to focus on the research area of limited and scalable, high-speed and efficient storage. Dynamic programming algorithm, as an optimization problem solving tool based on the characteristics of continuous time series analysis, has attracted widespread attention in this field. This article first introduces the dynamic programming theory and related concepts, and then tries to determine the optimal value based on the connection between the real-time indicators queried from the static database provided in the literature and the retrieval results obtained from historical queries. This article then tested the performance of the algorithm. The test results show that the algorithm has good performance in processing data. Its best calculation transmission time is within 3 seconds, and the transmission efficiency range is between 80% and 90%. The data integrity index is above 0.89, and the highest performance is 0.97. The five test results are very close to 1. The algorithm's complete optimization of the data is very significant. Although this article provides an in-depth study of the best computational methods for hybrid data blocks, there are still areas for improvement.
Chen et al. (Fri,) studied this question.