| 基于决策树模型的贵州降雹识别研究 |
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| 作者姓名： | 彭宇翔 文继芬 李皓 刘涛 唐辟如 郭茜 |
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| 作者单位： | 贵州省人工影响天气办公室,贵州 贵阳 550081;贵州省气象灾害防御技术中心,贵州 贵阳 550081;贵州省气象信息中心,贵州 贵阳 550002 |
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| 基金项目： | 贵州省科技计划项目(黔科合基础-ZK[2021]一般217)：基于风云卫星观测资料的冰雹天气识别研究；贵州省气象局科研业务项目(黔气科登[2020]07-13号):基于Logistic回归模型的贵州降雹识别指标研究;中国气象局人工影响天气中心业务项目：FY3/4卫星云特性产品在西南防雹增雨中的应用示范(一期)。 |
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| 摘 要： | 以FY-2G卫星反演产品为输入参数建立决策树模型,对2020年贵州降雹进行识别研究。收集了2020年贵州68个降雹点数据和68个未降雹点数据，从中随机选取58组降雹点和58组未降雹点数据用于建立决策树模型,剩余10组降雹点和10组未降雹点数据用于检验所建立模型的识别效果。结果表明,所建模型降雹识别准确率为80%,其中对10个降雹点识别准确率为70%,对10个未降雹点识别准确率为90%。
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| 关 键 词： | 决策树 冰雹 识别 检验 |
| 收稿时间： | 2021/6/9 0:00:00 |
| 修稿时间： | 2021/8/3 0:00:00 |
Hail Recognition in Guizhou Based on Decision Tree Model |
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| Authors: | pengyuxiang wenjifen lihao liutao tangpiru and guoxi |
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| Institution: | The Weather Modification Office of Guizhou Province,The Weather Modification Office of Guizhou Province,The Weather Modification Office of Guizhou Province,The Weather Modification Office of Guizhou Province,The Weather Modification Office of Guizhou Province,The Guizhou Meteorological Information Center |
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| Abstract: | In this paper, based on the FY-2G satellite inversion products as input parameters, a decision tree model is established to identify hail in Guizhou in 2020.Data of 68 hail spots and 68 non-hail spots in Guizhou in 2020 were collected.The data of 58 groups of hailspots and 58 groups of non-hail spots were selected at random to establish the decision tree model, and the remaining 10 groups of hail spots and 10 groups of non-hail spots were used to suggest the recognition effect of the established model.The results show that the recognition accuracy of the model is 80%, among which the recognition accuracy of 10 hail spots is 70%, and the recognition accuracy of 10 non-hail spots is 90%. |
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