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- W4200001421 abstract "With the rapid development of the national economy, the power system has higher and higher requirements for power supply stability. The traditional manual inspection method is dangerous, inefficient, and has poor data timeliness. Therefore, more and more people study how to put UAVs into power grid inspection. However, there is no good method to effectively process and predict the data collected by UAVs. To solve this problem, this paper uses the combination of mixed data prediction and support vector machine to predict the environmental data and judge the sensor state. For the final performance of the model, this paper chooses ACC as the standard. Experiments show that the prediction result of the model is indeed more accurate." @default.
- W4200001421 created "2021-12-31" @default.
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- W4200001421 date "2021-10-29" @default.
- W4200001421 modified "2023-09-27" @default.
- W4200001421 title "A Support Vector Machine Model based on Mixed Time Series Prediction" @default.
- W4200001421 doi "https://doi.org/10.1109/icdsca53499.2021.9650334" @default.
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