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作 者:蔡忠周 张继红 罗少辉 王军 CAI Zhongzhou;ZHANG Jihong;LUO Shaohui;WANG Jun(Qinghai Provincial Meteorological Disaster Prevention Technology Center,Xining 810000,China)
机构地区:[1]青海省气象灾害防御技术中心,青海西宁810000
出 处:《微型电脑应用》2024年第8期11-14,共4页Microcomputer Applications
基 金:青海省气象局面上项目(QXMS2023-41);海南州科技惠民计划项目(2023-KH01-A)。
摘 要:雷电灾害易损性风险等级具有模糊性和非线性,现有方法未对其进行充分考虑,导致权重设置存在明显缺陷,影响精准区划。为此,提出非线性干扰下雷电灾害易损性风险区划方法优化设计。针对以往检测数据,计算年平均雷击大地密度,分析雷电活动分布特征,以克服雷电灾害易损性风险等级的模糊性。构建易损性风险指标,将各指标及年平均雷击大地密度为输入构建雷电灾害易损性风险预测函数。为确保区划的准确性,采用自适应粒子群优化算法对指标风险因子权重进行粒子寻优,克服非线性影响,确定等级划分权重,实现等级风险区划。结果表明,所提方法区划结果与实际结果一致,且权重自适应性效果较佳,等错误率整体平均约为0.768%,区划准确性较高,具有可行性。The vulnerability risk level of lightning disaster has ambiguity and nonlinearity,and existing methods have not fully considered it,resulting in obvious defects in the weight setting process and affecting accurate zoning.To this end,an optimization design method for lightning disaster vulnerability risk zoning under nonlinear interference is proposed.Based on previous detection data,calculate the annual average lightning strike ground density and analyze the distribution characteristics of lightning activity to overcome the ambiguity of lightning disaster vulnerability risk levels.Construct vulnerability risk indicators and input each indicator and annual average lightning strike ground density to construct a lightning disaster vulnerability risk prediction function.To ensure the accuracy of zoning,an adaptive particle swarm optimization algorithm is adopted to optimize the weight of indicator risk factors through particle optimization,overcome nonlinear effects,determine the weight of level division,and achieve level risk zoning.The results show that the proposed method’s zoning results are consistent with the actual results,and the weight adaptability effect is good.The overall average error rate is about 0.768%,and the zoning accuracy is high,which is feasible.
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