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
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
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.
