Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the mos...Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the most common convective weather phenomena that can cause severe damage.Short-range forecasting of SHR is an important part of operational severe weather prediction.In the present study,an improved objective SHR forecasting scheme was developed by adopting the ingredients-based methodology and using the fuzzy logic approach.The 1.0°×1.0°National Centers for Environmental Prediction(NCEP)final analysis data and the ordinary rainfall(0.1-19.9 mm h-1)and SHR observational data from 411 stations were used in the improved scheme.The best lifted index,the total precipitable water,the 925 hPa specific humidity(Q 925),and the 925 hPa divergence(DIV 925)were selected as predictors based on objective analysis.Continuously distributed membership functions of predictors were obtained based on relative frequency analysis.The weights of predictors were also objectively determined.Experiments with a typhoon SHR case and a spring SHR case show that the main possible areas could be captured by the improved scheme.Verification of SHR forecasts within 96 hours with NCEP global forecasts 1.0°×1.0°data initiated at 08:00 Beijing Time during the warm seasons in 2015 show the results were improved from both deterministic and probabilistic perspectives.This study provides an objectively feasible choice for short-range guidance forecasts of SHR.The scheme can be applied to other convective phenomena.展开更多
为提高浮动车数据中异常数据检测能力及不同载客状态下的模型检测分析能力,提出基于S-DTA-IIForest(Summation&Difference Third Order Average&Improvement-Isolation Forest)的浮动车数据异常检测算法。构建由相邻两项求和(S...为提高浮动车数据中异常数据检测能力及不同载客状态下的模型检测分析能力,提出基于S-DTA-IIForest(Summation&Difference Third Order Average&Improvement-Isolation Forest)的浮动车数据异常检测算法。构建由相邻两项求和(S)、三阶求和平均差分(DTA)的二维度空间SDTA特征向量;提出差额累计更新和动态区分辨识的改进孤立森林IIForest算法,通过设置停止阈值参数,避免当出现新样本异常值分数大于停止阈值时,仅更新样本不更新孤立森林模型的问题,设计每个二叉树区分辨识度参数,区分辨识度位于停止区间时停止二叉树生长,提高算法收敛性能,以ROC(Receiver Operating Characteristic)曲线下面积AUC(Area Under ROC Cure)、F1-score为指标对模型精度进行对比分析,并以重庆市中心城区学府大道开展实例验证。结果表明:本文S-DTA-IIForest组合算法AUC、F1-score分别为86.63%、0.89,AUC较传统孤立森林IForest(Isolation Forest)提高32.4%,运行效率提高1.29%,具有收敛速度更快、精度更高的优势,载客条件下模型AUC、F1-score较未载客分别提高7.7%、10.8%,组合算法对载客数据有更高的检测精度,且未载客状态数据异常率较载客状态增加71.4%,未载客数据异常率更高。展开更多
为合理地解决环境敏感区铁路线路方案综合优选问题,研究顾及环境敏感特征的铁路线路方案优选方法 .首先,基于文献调研和环境敏感区特征探析,分析总结影响线路方案的因素,构建涵盖4大方面18项指标的顾及环境敏感特征的铁路线路方案优选...为合理地解决环境敏感区铁路线路方案综合优选问题,研究顾及环境敏感特征的铁路线路方案优选方法 .首先,基于文献调研和环境敏感区特征探析,分析总结影响线路方案的因素,构建涵盖4大方面18项指标的顾及环境敏感特征的铁路线路方案优选指标体系.其次,在专家经验主观赋权和工程信息客观赋权的基础上,运用灰色关联分析理论进行组合赋权.然后,结合改进优劣解距离法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)确定各线路方案的相对贴近度,进而实现线路方案优选.最后,以新建铁路西宁至成都线合作至郎木寺段线路方案选择为例进行优选方法验证.研究结果表明:该区段线路的4个备选方案的相对贴近度依次为0.527 9,0.523 6,0.508 7,0.522 7,方案一的相对贴近度最大为最优方案,基于本方法的优选结果与实际专家论证结果一致;与传统TOPSIS比较,基于改进TOPSIS的运算结果避免了计算结果受单方面优势指标影响的弊端,在运算过程中将线路方案涉及的极端优劣指标进行综合权衡考量,得到的运算结果更贴近实际情况.研究成果可为未来环境敏感区线路方案优选问题提供一种新的优选思路.展开更多
为提高山区隧道施工场地布置方案决策的准确性,以牛栾村隧道六种施工场地布置方案为例,提出了基于改进灰靶的方案优选模型。首先,通过分析场地布置方案影响因素,构建了以方案可行性、方案经济性、环境影响和社会效益影响为核心的评价指...为提高山区隧道施工场地布置方案决策的准确性,以牛栾村隧道六种施工场地布置方案为例,提出了基于改进灰靶的方案优选模型。首先,通过分析场地布置方案影响因素,构建了以方案可行性、方案经济性、环境影响和社会效益影响为核心的评价指标体系;其次,采用云模型将定性指标定量描述,并运用CRITIC(criteria importance though intercriteria correlation)确定指标权重;最后以灰色关联差异信息值为基础,结合欧几里得理论计算修正的加权靶心距,通过对比靶心距实现方案优选,并采用单因素轮换法(one-at-a-time,OAT)进行了指标敏感性分析。结果表明:最优方案的加权靶心距为0.610,评选出的方案与实际一致,并分析出“地形地貌改变”为对方案评选影响最大的指标。可见,该方法呈现了各方案的优劣,使山区隧道施工场地布置方案评选更科学、合理。展开更多
Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the p...Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.展开更多
基金Key R&D Program of Xizang Autonomous Region(XZ202101ZY0004G)National Natural Science Foundation of China(U2142202)+1 种基金National Key R&D Program of China(2022YFC3004104)Key Innovation Team of China Meteor-ological Administration(CMA2022ZD07)。
文摘Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the most common convective weather phenomena that can cause severe damage.Short-range forecasting of SHR is an important part of operational severe weather prediction.In the present study,an improved objective SHR forecasting scheme was developed by adopting the ingredients-based methodology and using the fuzzy logic approach.The 1.0°×1.0°National Centers for Environmental Prediction(NCEP)final analysis data and the ordinary rainfall(0.1-19.9 mm h-1)and SHR observational data from 411 stations were used in the improved scheme.The best lifted index,the total precipitable water,the 925 hPa specific humidity(Q 925),and the 925 hPa divergence(DIV 925)were selected as predictors based on objective analysis.Continuously distributed membership functions of predictors were obtained based on relative frequency analysis.The weights of predictors were also objectively determined.Experiments with a typhoon SHR case and a spring SHR case show that the main possible areas could be captured by the improved scheme.Verification of SHR forecasts within 96 hours with NCEP global forecasts 1.0°×1.0°data initiated at 08:00 Beijing Time during the warm seasons in 2015 show the results were improved from both deterministic and probabilistic perspectives.This study provides an objectively feasible choice for short-range guidance forecasts of SHR.The scheme can be applied to other convective phenomena.
文摘为提高浮动车数据中异常数据检测能力及不同载客状态下的模型检测分析能力,提出基于S-DTA-IIForest(Summation&Difference Third Order Average&Improvement-Isolation Forest)的浮动车数据异常检测算法。构建由相邻两项求和(S)、三阶求和平均差分(DTA)的二维度空间SDTA特征向量;提出差额累计更新和动态区分辨识的改进孤立森林IIForest算法,通过设置停止阈值参数,避免当出现新样本异常值分数大于停止阈值时,仅更新样本不更新孤立森林模型的问题,设计每个二叉树区分辨识度参数,区分辨识度位于停止区间时停止二叉树生长,提高算法收敛性能,以ROC(Receiver Operating Characteristic)曲线下面积AUC(Area Under ROC Cure)、F1-score为指标对模型精度进行对比分析,并以重庆市中心城区学府大道开展实例验证。结果表明:本文S-DTA-IIForest组合算法AUC、F1-score分别为86.63%、0.89,AUC较传统孤立森林IForest(Isolation Forest)提高32.4%,运行效率提高1.29%,具有收敛速度更快、精度更高的优势,载客条件下模型AUC、F1-score较未载客分别提高7.7%、10.8%,组合算法对载客数据有更高的检测精度,且未载客状态数据异常率较载客状态增加71.4%,未载客数据异常率更高。
文摘为合理地解决环境敏感区铁路线路方案综合优选问题,研究顾及环境敏感特征的铁路线路方案优选方法 .首先,基于文献调研和环境敏感区特征探析,分析总结影响线路方案的因素,构建涵盖4大方面18项指标的顾及环境敏感特征的铁路线路方案优选指标体系.其次,在专家经验主观赋权和工程信息客观赋权的基础上,运用灰色关联分析理论进行组合赋权.然后,结合改进优劣解距离法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)确定各线路方案的相对贴近度,进而实现线路方案优选.最后,以新建铁路西宁至成都线合作至郎木寺段线路方案选择为例进行优选方法验证.研究结果表明:该区段线路的4个备选方案的相对贴近度依次为0.527 9,0.523 6,0.508 7,0.522 7,方案一的相对贴近度最大为最优方案,基于本方法的优选结果与实际专家论证结果一致;与传统TOPSIS比较,基于改进TOPSIS的运算结果避免了计算结果受单方面优势指标影响的弊端,在运算过程中将线路方案涉及的极端优劣指标进行综合权衡考量,得到的运算结果更贴近实际情况.研究成果可为未来环境敏感区线路方案优选问题提供一种新的优选思路.
文摘为提高山区隧道施工场地布置方案决策的准确性,以牛栾村隧道六种施工场地布置方案为例,提出了基于改进灰靶的方案优选模型。首先,通过分析场地布置方案影响因素,构建了以方案可行性、方案经济性、环境影响和社会效益影响为核心的评价指标体系;其次,采用云模型将定性指标定量描述,并运用CRITIC(criteria importance though intercriteria correlation)确定指标权重;最后以灰色关联差异信息值为基础,结合欧几里得理论计算修正的加权靶心距,通过对比靶心距实现方案优选,并采用单因素轮换法(one-at-a-time,OAT)进行了指标敏感性分析。结果表明:最优方案的加权靶心距为0.610,评选出的方案与实际一致,并分析出“地形地貌改变”为对方案评选影响最大的指标。可见,该方法呈现了各方案的优劣,使山区隧道施工场地布置方案评选更科学、合理。
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.51575528)the Science Foundation of China University of Petroleum,Beijing(No.2462022QEDX011).
文摘Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.
