Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Curren...Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Current researches mostly use traditional machine learning methods to extract features of weather scenes,and clustering algorithms to divide similar scenes.Inspired by the excellent performance of deep learning in image recognition,this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering(IDCEC),which uses the com-bination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image,retaining useful information to the greatest extent,and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area.Finally,term-inal area of Guangzhou Airport is selected as the research object,the method pro-posed in this article is used to classify historical weather data in similar scenes,and the performance is compared with other state-of-the-art methods.The experi-mental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather;at the same time,compared with the actualflight volume in the Guangz-hou terminal area,IDCEC's recognition results of similar weather scenes are con-sistent with the recognition of experts in thefield.展开更多
In order to improve the recognition accuracy of similar weather scenarios(SWSs)in terminal area,a recognition model for SWS based on contrastive learning(SWS-CL)is proposed.Firstly,a data augmentation method is design...In order to improve the recognition accuracy of similar weather scenarios(SWSs)in terminal area,a recognition model for SWS based on contrastive learning(SWS-CL)is proposed.Firstly,a data augmentation method is designed to improve the number and quality of weather scenarios samples according to the characteristics of convective weather images.Secondly,in the pre-trained recognition model of SWS-CL,a loss function is formulated to minimize the distance between the anchor and positive samples,and maximize the distance between the anchor and the negative samples in the latent space.Finally,the pre-trained SWS-CL model is fine-tuned with labeled samples to improve the recognition accuracy of SWS.The comparative experiments on the weather images of Guangzhou terminal area show that the proposed data augmentation method can effectively improve the quality of weather image dataset,and the proposed SWS-CL model can achieve satisfactory recognition accuracy.It is also verified that the fine-tuned SWS-CL model has obvious advantages in datasets with sparse labels.展开更多
Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits o...Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits of multi terminal DC (MTDC) tie lines as compared to the traditional HVAC forms the main objective of this paper. Probabilistic load flow (PLF) is applied to determine the system parameters while the uncertainties are modelled using Scenario Based Method (SBM). The simulation results reveal that with the use of MTDC tie lines, the frequency and voltage stability in the MAMODED with renewable energy sources (RES) are enhanced while keeping the MTDC power exchange interface nodes at secure levels.展开更多
Continental reconstructions in Central Asia are represented by orogenesis along some large orogenic belts in the Altaid collage （Fig. 1 ） or Central Asian Orogenic Belt （CAOB）, which separate the East European and...Continental reconstructions in Central Asia are represented by orogenesis along some large orogenic belts in the Altaid collage （Fig. 1 ） or Central Asian Orogenic Belt （CAOB）, which separate the East European and Siberian cratons to the north from the Tarim and North China cratons to the south （$eng0r et al,, 1993; Jahn et al., 2004; Windley et al., 2007; Qu et al., 2008; Xiao et al., 2010; Xiao and Santosh, 2014）. The Altaid Collage was characterized by complex long tectonic and structural evolution from at least ca. 1.0 Ga to late Paleozoic-early Mesozoic with considerable continental growth （Khain et al., 2002; Jahn et al., 2004; Xiao et al., 2009, 2014; KrOner et al., 2014）, followed by Cenozoic intracontinental evolution related to far-field effect of the collision of the In- dian Plate to the Eurasian Accompanying with these complex world-class ore deposits developed 2001; Goldfarb et al., 2003, 2014）. Plate （Cunningham, 2005）. geodynamic evolutions, many （Qin, 2000; Yakubchuk et al,2001; Goldfarb et al., 2003, 2014）.展开更多
Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning are...Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning areas, transition areas, and activity areas of work zone, than the termination areas, where drivers might play less attention to safety threats. In this study, the vehicle-to-vehicle communication based left turn warning system was applied at a work zone termination area, which is immediately followed by a T-intersection. The work-zone is located on the minor road side, while left turn vehicles will be appearing from the major street through the said T-intersection. A smart phone application was designed using Android coding system to provide several types of warning messages to drivers. Corresponding scenarios were designed in a driving simulator, and 20 subjects were recruited to participate in the simulation test followed by a questionnaire survey. The subjects received a warning message when driving to the termination area of a work zone on the coming left turn vehicles. Twenty test drivers’ driving speed, acceleration rates, and break reaction distance to the warning messages were studied in four different scenarios. Results show that the smartphone application has a great impact on driving behaviors, especially the female voice and the beep tone warning, which are recommended for possible field tests. Besides, the developed smartphone applications can be further updated for practical applications of similar needs.展开更多
针对点融合系统中航班调度问题,构建航班进场排序的二维元胞自动机模型,模拟先来先服务(first come first service, FCFS)和滑动窗口(sliding window, SDW)策略下的航班排序过程,对比不同策略下的终端区运行效率。实验结果表明:若都采用...针对点融合系统中航班调度问题,构建航班进场排序的二维元胞自动机模型,模拟先来先服务(first come first service, FCFS)和滑动窗口(sliding window, SDW)策略下的航班排序过程,对比不同策略下的终端区运行效率。实验结果表明:若都采用FCFS,使用中国民航航空器尾流重新分类标准(RECAT-CN)代替现行尾流间隔,进场航班流在点融合系统中的总运行时间减少了98 s,运行效率提升了4.3%;若都使用RECAT-CN间隔标准,采用SDW优化后的航班进场序列,较FCFS的总运行时间减少了193 s,运行效率提升了8.5%;点融合技术和RECAT-CN间隔标准可以实现终端区运行安全和效率的同步提升。展开更多
为了针对性地制定后续优化措施,以降低多机场终端区内航班延误所带来的不利影响,并提高多机场系统内各机场的运营效率,进行多机场终端区航班延误的预测研究。首先,考虑多机场终端区交通态势对航班延误的影响,在对多机场终端区交通态势...为了针对性地制定后续优化措施,以降低多机场终端区内航班延误所带来的不利影响,并提高多机场系统内各机场的运营效率,进行多机场终端区航班延误的预测研究。首先,考虑多机场终端区交通态势对航班延误的影响,在对多机场终端区交通态势进行分析的基础上,建立6个描述终端区交通态势的指标。接着,构建反向传播(back propagation,BP)神经网络航班延误预测模型,将终端区交通态势指标、航班信息和天气环境数据等作为输入,航班延误时间作为输出,并利用粒子群优化算法(particle swarm optimization,PSO)优化BP神经网络进行训练。通过实例验证和分析,基于多机场终端区交通态势的航班延误预测能够有效提高预测准确率,同时,通过粒子群优化BP神经网络的预测模型预测准确率均高于一般的考虑交通态势的BP和遗传算法优化的BP神经网络模型(genetic algorithm and back propagation,GA-BP)。展开更多
基金supported by the Fundamental Research Funds for the CentralUniversities under Grant NS2020045. Y.L.G received the grant.
文摘Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Current researches mostly use traditional machine learning methods to extract features of weather scenes,and clustering algorithms to divide similar scenes.Inspired by the excellent performance of deep learning in image recognition,this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering(IDCEC),which uses the com-bination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image,retaining useful information to the greatest extent,and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area.Finally,term-inal area of Guangzhou Airport is selected as the research object,the method pro-posed in this article is used to classify historical weather data in similar scenes,and the performance is compared with other state-of-the-art methods.The experi-mental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather;at the same time,compared with the actualflight volume in the Guangz-hou terminal area,IDCEC's recognition results of similar weather scenes are con-sistent with the recognition of experts in thefield.
基金supported by the Fundamental Research Funds for the Central Universities(NOS.NS2019054,NS2020045)。
文摘In order to improve the recognition accuracy of similar weather scenarios(SWSs)in terminal area,a recognition model for SWS based on contrastive learning(SWS-CL)is proposed.Firstly,a data augmentation method is designed to improve the number and quality of weather scenarios samples according to the characteristics of convective weather images.Secondly,in the pre-trained recognition model of SWS-CL,a loss function is formulated to minimize the distance between the anchor and positive samples,and maximize the distance between the anchor and the negative samples in the latent space.Finally,the pre-trained SWS-CL model is fine-tuned with labeled samples to improve the recognition accuracy of SWS.The comparative experiments on the weather images of Guangzhou terminal area show that the proposed data augmentation method can effectively improve the quality of weather image dataset,and the proposed SWS-CL model can achieve satisfactory recognition accuracy.It is also verified that the fine-tuned SWS-CL model has obvious advantages in datasets with sparse labels.
文摘Security constrained multi area multi objective dynamic economic dispatch (SCMAMODED) with renewable energy (RE) and all the possible MTDC stability constraints is formulated for the first time. The stability merits of multi terminal DC (MTDC) tie lines as compared to the traditional HVAC forms the main objective of this paper. Probabilistic load flow (PLF) is applied to determine the system parameters while the uncertainties are modelled using Scenario Based Method (SBM). The simulation results reveal that with the use of MTDC tie lines, the frequency and voltage stability in the MAMODED with renewable energy sources (RES) are enhanced while keeping the MTDC power exchange interface nodes at secure levels.
基金financially supported by the Natural National Science Foundation of China(Grant Nos.41230207,41202150, 41472192,41390441 and 41190075)
文摘Continental reconstructions in Central Asia are represented by orogenesis along some large orogenic belts in the Altaid collage （Fig. 1 ） or Central Asian Orogenic Belt （CAOB）, which separate the East European and Siberian cratons to the north from the Tarim and North China cratons to the south （$eng0r et al,, 1993; Jahn et al., 2004; Windley et al., 2007; Qu et al., 2008; Xiao et al., 2010; Xiao and Santosh, 2014）. The Altaid Collage was characterized by complex long tectonic and structural evolution from at least ca. 1.0 Ga to late Paleozoic-early Mesozoic with considerable continental growth （Khain et al., 2002; Jahn et al., 2004; Xiao et al., 2009, 2014; KrOner et al., 2014）, followed by Cenozoic intracontinental evolution related to far-field effect of the collision of the In- dian Plate to the Eurasian Accompanying with these complex world-class ore deposits developed 2001; Goldfarb et al., 2003, 2014）. Plate （Cunningham, 2005）. geodynamic evolutions, many （Qin, 2000; Yakubchuk et al,2001; Goldfarb et al., 2003, 2014）.
文摘Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning areas, transition areas, and activity areas of work zone, than the termination areas, where drivers might play less attention to safety threats. In this study, the vehicle-to-vehicle communication based left turn warning system was applied at a work zone termination area, which is immediately followed by a T-intersection. The work-zone is located on the minor road side, while left turn vehicles will be appearing from the major street through the said T-intersection. A smart phone application was designed using Android coding system to provide several types of warning messages to drivers. Corresponding scenarios were designed in a driving simulator, and 20 subjects were recruited to participate in the simulation test followed by a questionnaire survey. The subjects received a warning message when driving to the termination area of a work zone on the coming left turn vehicles. Twenty test drivers’ driving speed, acceleration rates, and break reaction distance to the warning messages were studied in four different scenarios. Results show that the smartphone application has a great impact on driving behaviors, especially the female voice and the beep tone warning, which are recommended for possible field tests. Besides, the developed smartphone applications can be further updated for practical applications of similar needs.
文摘针对点融合系统中航班调度问题,构建航班进场排序的二维元胞自动机模型,模拟先来先服务(first come first service, FCFS)和滑动窗口(sliding window, SDW)策略下的航班排序过程,对比不同策略下的终端区运行效率。实验结果表明:若都采用FCFS,使用中国民航航空器尾流重新分类标准(RECAT-CN)代替现行尾流间隔,进场航班流在点融合系统中的总运行时间减少了98 s,运行效率提升了4.3%;若都使用RECAT-CN间隔标准,采用SDW优化后的航班进场序列,较FCFS的总运行时间减少了193 s,运行效率提升了8.5%;点融合技术和RECAT-CN间隔标准可以实现终端区运行安全和效率的同步提升。
文摘为了针对性地制定后续优化措施,以降低多机场终端区内航班延误所带来的不利影响,并提高多机场系统内各机场的运营效率,进行多机场终端区航班延误的预测研究。首先,考虑多机场终端区交通态势对航班延误的影响,在对多机场终端区交通态势进行分析的基础上,建立6个描述终端区交通态势的指标。接着,构建反向传播(back propagation,BP)神经网络航班延误预测模型,将终端区交通态势指标、航班信息和天气环境数据等作为输入,航班延误时间作为输出,并利用粒子群优化算法(particle swarm optimization,PSO)优化BP神经网络进行训练。通过实例验证和分析,基于多机场终端区交通态势的航班延误预测能够有效提高预测准确率,同时,通过粒子群优化BP神经网络的预测模型预测准确率均高于一般的考虑交通态势的BP和遗传算法优化的BP神经网络模型(genetic algorithm and back propagation,GA-BP)。
