Transportation of floating structures for long distance has always been associated with the use of heavy semi transport vessel. The requirements of this type of vessel are always special, and its availability is limit...Transportation of floating structures for long distance has always been associated with the use of heavy semi transport vessel. The requirements of this type of vessel are always special, and its availability is limited. To prepare for the future development of the South China Sea deepwater projects, COOEC has recently built a heavy lift transport vessel - Hai Yang Shi You 278 （HYSY278）. This semi-submersible vessel has displacement capacity of 50k DWT, and a breath of 42 m. Understanding the vessel＇s applicability and preparing its use for future deepwater projects are becoming imminent need. This paper reviews the critical issues associated with the floating structure transportation and performs detailed analysis of two designed floating structures during transportation. The newly built COOEC transportation vessel HYSY278 will be used to dry transport the floating structures from COOEC fabrication yard in Qingdao to the oil field in the South China Sea. The entire process will start with load-out/float-offthe floating structures from the construction sites, offload the platform from the vessel if needed, dry transport floating structures through a long distance, and finally offload the platform. Both hydrodynamic and struc^tral analyses are performed to evaluate transport vessel and floating structures. Critical issues associated with the transportation and offloading of platform from the vessel will be studied in detail. Detailed study is performed to evaluate the response of the system during this phase and additional work needed to make the vessel feasible for use of this purpose. The results demonstrate that with proper modifications, HYSY278 can effectively be used for transporting structures with proper arrangement and well-prepared operation. The procedure and details are presented on the basis of study results. Special attentions associated with future use will also be discussed based on the results from analysis.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
A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways,...A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data （FCD） system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.展开更多
基金funded by the State Key Project "Installation Technical Study for Deepwater Floating Structure"
文摘Transportation of floating structures for long distance has always been associated with the use of heavy semi transport vessel. The requirements of this type of vessel are always special, and its availability is limited. To prepare for the future development of the South China Sea deepwater projects, COOEC has recently built a heavy lift transport vessel - Hai Yang Shi You 278 （HYSY278）. This semi-submersible vessel has displacement capacity of 50k DWT, and a breath of 42 m. Understanding the vessel＇s applicability and preparing its use for future deepwater projects are becoming imminent need. This paper reviews the critical issues associated with the floating structure transportation and performs detailed analysis of two designed floating structures during transportation. The newly built COOEC transportation vessel HYSY278 will be used to dry transport the floating structures from COOEC fabrication yard in Qingdao to the oil field in the South China Sea. The entire process will start with load-out/float-offthe floating structures from the construction sites, offload the platform from the vessel if needed, dry transport floating structures through a long distance, and finally offload the platform. Both hydrodynamic and struc^tral analyses are performed to evaluate transport vessel and floating structures. Critical issues associated with the transportation and offloading of platform from the vessel will be studied in detail. Detailed study is performed to evaluate the response of the system during this phase and additional work needed to make the vessel feasible for use of this purpose. The results demonstrate that with proper modifications, HYSY278 can effectively be used for transporting structures with proper arrangement and well-prepared operation. The procedure and details are presented on the basis of study results. Special attentions associated with future use will also be discussed based on the results from analysis.
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。
基金The Project of Research on Technologyand Devices for Traffic Guidance (Vehicle Navigation)System of Beijing Municipal Commission of Science and Technology(No H030630340320)the Project of Research on theIntelligence Traffic Information Platform of Beijing Education Committee
文摘A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data （FCD） system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.
