暴雨洪水管理模型(storm water management model,SWMM)的不确定参数在一定程度上影响着内涝模拟的精度,因此以中山市某研究区域为例,计算SWMM模型参数的初始值,采用最大互信息系数和偏相关系数探究短历时、长历时不同重现期下对径流总...暴雨洪水管理模型(storm water management model,SWMM)的不确定参数在一定程度上影响着内涝模拟的精度,因此以中山市某研究区域为例,计算SWMM模型参数的初始值,采用最大互信息系数和偏相关系数探究短历时、长历时不同重现期下对径流总量、出流总量、峰值流量和峰现时间敏感的参数,并利用熵权法确定2种方法的权重进行综合评价,结合综合分析得到的敏感参数和偏相关分析得到的变量之间的正负相关关系,选取8场历史降雨对模型进行率定与验证。结果表明:2种方法得到的各重现期下敏感参数并不完全一致;综合分析发现不同重现期要考虑的敏感参数略有不同,且各重现期最敏感参数与最大互信息系数的结果一致;P=10 a、20 a同一重现期不同降雨历时下敏感参数存在较大差异;模型模拟的管网井下液位的纳什效率系数均大于0.7,峰现时间误差均小于等于30 min,峰值相对误差的绝对值均小于3.5%。通过深入分析模型参数的不确定性,可提高参数率定效率和模型的准确度。展开更多
为快速、准确预测接触网复合绝缘子临界污闪电压,减少人工污秽试验工作量,提出了一种复合绝缘子污秽闪络电压预测模型。首先,利用黄金正弦(golden sine algorithm,GSA)与分段线性混沌映射(piecewise linear chaotic map,PWLCM)改进的减...为快速、准确预测接触网复合绝缘子临界污闪电压,减少人工污秽试验工作量,提出了一种复合绝缘子污秽闪络电压预测模型。首先,利用黄金正弦(golden sine algorithm,GSA)与分段线性混沌映射(piecewise linear chaotic map,PWLCM)改进的减法平均优化器(subtraction average based optimizer,SABO)算法增强反向传播(back propagation,BP)神经网络的性能;其次,利用人工污秽试验获取10种不同复合绝缘子的闪络电压,收集相关试验参数;再次,依据Obenaus模型对复合绝缘子污秽闪络表现进行分析,利用斯皮尔曼(Spearman)相关系数法筛选出与复合绝缘子临界污闪电压密切相关的4个参数作为预测模型的输入特征量,以预测复合绝缘子临界污闪电压;最后,利用五折交叉验证法对预测模型进行综合评估,并与常用智能优化算法预测模型的预测结果进行比较。结果表明:GSABO-BP模型预测复合绝缘子污闪电压平均绝对误差为1.244 kV,平均绝对百分比误差为2.25%,模型可决系数稳定在0.98以上;与改进前的SABO-BP模型相比,预测值平均误差下降67.80%。GSABO-BP模型在复合绝缘子污闪电压预测上具有较高的预测精准度,对电气化铁路供电系统的防污保护工作具有重要意义。展开更多
【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子...【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子与其他污染因子进行斯皮尔曼相关性分析。【结果】采用阶梯型隶属度函数的模糊综合评价法相较AQI(Ambient Air Quality Index)和内梅罗指数法能够综合所有污染因子的作用更加全面评价环境空气质量,且长治市2017—2022共6年间环境空气质量状况在逐渐好转。长治市的首要污染因子为PM_(10),且与PM_(2.5)、SO_(2)、NO_(2)、CO均具有相关性,相关性依次递减,而与O_(3)不具相关性。通过污染因子时间分布特征分析发现,每年一、四季度PM_(2.5)、PM_(10)、CO、NO_(2)、SO_(2)的浓度会上升,二、三季度5种污染因子的浓度呈现下降趋势,并且一、四季度5项污染因子的浓度值高于二、三季度。新冠肺炎疫情暴发期间,所有污染因子均呈现下降趋势,且CO浓度的下降趋势最为明显。展开更多
In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indi...In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.展开更多
文摘为快速、准确预测接触网复合绝缘子临界污闪电压,减少人工污秽试验工作量,提出了一种复合绝缘子污秽闪络电压预测模型。首先,利用黄金正弦(golden sine algorithm,GSA)与分段线性混沌映射(piecewise linear chaotic map,PWLCM)改进的减法平均优化器(subtraction average based optimizer,SABO)算法增强反向传播(back propagation,BP)神经网络的性能;其次,利用人工污秽试验获取10种不同复合绝缘子的闪络电压,收集相关试验参数;再次,依据Obenaus模型对复合绝缘子污秽闪络表现进行分析,利用斯皮尔曼(Spearman)相关系数法筛选出与复合绝缘子临界污闪电压密切相关的4个参数作为预测模型的输入特征量,以预测复合绝缘子临界污闪电压;最后,利用五折交叉验证法对预测模型进行综合评估,并与常用智能优化算法预测模型的预测结果进行比较。结果表明:GSABO-BP模型预测复合绝缘子污闪电压平均绝对误差为1.244 kV,平均绝对百分比误差为2.25%,模型可决系数稳定在0.98以上;与改进前的SABO-BP模型相比,预测值平均误差下降67.80%。GSABO-BP模型在复合绝缘子污闪电压预测上具有较高的预测精准度,对电气化铁路供电系统的防污保护工作具有重要意义。
文摘【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子与其他污染因子进行斯皮尔曼相关性分析。【结果】采用阶梯型隶属度函数的模糊综合评价法相较AQI(Ambient Air Quality Index)和内梅罗指数法能够综合所有污染因子的作用更加全面评价环境空气质量,且长治市2017—2022共6年间环境空气质量状况在逐渐好转。长治市的首要污染因子为PM_(10),且与PM_(2.5)、SO_(2)、NO_(2)、CO均具有相关性,相关性依次递减,而与O_(3)不具相关性。通过污染因子时间分布特征分析发现,每年一、四季度PM_(2.5)、PM_(10)、CO、NO_(2)、SO_(2)的浓度会上升,二、三季度5种污染因子的浓度呈现下降趋势,并且一、四季度5项污染因子的浓度值高于二、三季度。新冠肺炎疫情暴发期间,所有污染因子均呈现下降趋势,且CO浓度的下降趋势最为明显。
基金Project(50774095) supported by the National Natural Science Foundation of ChinaProject(200449) supported by the National Outstanding Doctoral Dissertations Special Funds of China
文摘In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.
