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- W4283778460 abstract "The thesis is mayor in based on the evaluation of base station interference sources in multiple dimensions by China Unicom Shanghai Branch. Based on the value mining of multiple data sources such as KPI/XDR/MDT, it closely integrates the traditional interference source investigation process and big data/machine learning Technology. At the same time, combined with BPNN neural network, the interference source and interference type can be identified intelligently. By using the BFL boundary point fitting algorithm, the interference source can be detected, classified and simulated. At the same time, a set of interference source overall optimization scheme is given." @default.
- W4283778460 created "2022-07-03" @default.
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- W4283778460 date "2022-07-02" @default.
- W4283778460 modified "2023-09-26" @default.
- W4283778460 title "Research on Interference Source Identification and Location Based on Big Data and Deep Learning" @default.
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- W4283778460 doi "https://doi.org/10.1007/978-981-19-3387-5_165" @default.
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