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首页> 外文期刊>International journal of information retrieval research >Distributed Database Management With Integration of Blockchain and Long Short-Term Memory
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Distributed Database Management With Integration of Blockchain and Long Short-Term Memory

机译：分布式数据库管理，具有区块链的集成和长期内存

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摘要

Supply chain management is the broad range of activities required to plan, control, and execute the flow of a product. As a less corruptible and more automated alternative to traditional databases, blockchains are well suited to the complicated record-keeping. However distributed database management system is a centralized software system; the blockchain technology can overcome the problem of synchronization between multiple databases; it also ensures that integrity problems are solved. In the proposed model, Ethereum blockchain is used to solve a few major supply chain problems to manage a distributed database. The model has incorporated techniques to predict the rise and fall of the demand for the medicine in the market by using machine learning algorithms such as linear regression and LSTM; also, the trend predicted by both the models has been compared. The result shows that while using linear regression the predicted trend is not very accurate and cannot trace the actual trend closely whereas BLSTM has performed well in predicting the trends of time series data.
机译：供应链管理是规划，控制和执行产品流程所需的广泛活动。作为传统数据库的较少腐败性和更自动的替代品，区块链非常适合复杂的记录保存。但是分布式数据库管理系统是一个集中式软件系统;区块链技术可以克服多个数据库之间同步的问题;它还确保解决完整性问题。在所提出的模型中，Ethereum BlockChinain用于解决一些主要的供应链问题来管理分布式数据库。该模型通过使用线性回归和LSTM等机器学习算法，包括预测市场上药物需求的上升和下降的技术;此外，两种模型预测的趋势已经进行了比较。结果表明，在使用线性回归时，预测的趋势不是非常准确的，并且不能紧密地追踪实际趋势，而BLSTM在预测时间序列数据的趋势时表现良好。

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