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• W3111264080 abstract "The continuously increasing number of connected smart devices has led to the emergence of a crucial fault detection challenge to the Internet of Things (IoT). In this study, we aim to identify a method for the effective detection of faults in IoT devices. An IoT network model is first established, and a data edge verification mechanism based on blockchain is proposed; the blockchain is used to ensure that the data cannot be tampered with, and their accuracy is verified using the edge. Finally, a data set accuracy weighted random forest based on particle swarm optimization is proposed. The simulation results demonstrate that the proposed detection algorithm is both effective and efficient." @default.
• W3111264080 created "2020-12-21" @default.
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• W3111264080 date "2021-02-15" @default.
• W3111264080 modified "2023-09-25" @default.
• W3111264080 title "A Data Set Accuracy Weighted Random Forest Algorithm for IoT Fault Detection Based on Edge Computing and Blockchain" @default.
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• W3111264080 doi "https://doi.org/10.1109/jiot.2020.3044934" @default.
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