基于用电数据挖掘分析的非法大麻种植检测
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1.长沙理工大学电气与信息工程学院;2.国网宁夏电力有限公司

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Data Mining of Metering Usage Data to Detect Indoor Cultivation of Cannabis
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1.Changsha University of Science and Technology;2.Marketing Service Center of State Grid Ningxia Electric Power Company

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    摘要:

    在欧美大麻合法化风潮影响下,国内开始批量出现室内种植大麻的违法现象.利用室内种植大麻需大量消耗电能且用电行为具有规律性的特点,提出了一种基于用电功率频率分布相对熵的室内大麻种植检测方法。首先分析了室内种植大麻的用电需求规律特征,并搭建实验室仿真环境进行了种植大麻用电数据的模拟产生。然后比对居民用户和室内大麻种植用电行为在时域、频域及具体指标项上的差异;此基础上,制定了根据用电功率频率分布相对熵等指标识别非法大麻种植的检测流程。基于爱尔兰居民用电数据的测试分析表明所提方法可有效识别和排除正常居民用户,提高大麻种植异常检测的靶向性。

    Abstract:

    Under the dissemination of legalization of cannabis in USA and EU, cultivation of cannabis indoor got popular in China in recent years. Since cultivation of cannabis indoor result in large number of electricity consumption with distinct feature of electricity usage, relative entropy of the frequency distribution of electricity usage based approach is developed to identify anomaly users in this article. We produce electricity usage data of cultivate cannabis indoor with experiment. The statistics of temporal and frequency features of cultivation of cannabis indoor, as well as residential users are analyzed for comparison. Thereafter, the flowchart to identify anomaly users with cultivation of cannabis indoor is developed. Numerical simulation of electricity usage data of Irish residents suggests that the proposed approach can distinguish residential users and anomaly users. It is helpful to identify illegal user cultivating cannabis indoor.

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  • 收稿日期:2021-06-02
  • 最后修改日期:2021-07-15
  • 录用日期:2021-09-11
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