It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly eval...It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.展开更多
Automated image classification and visual interpretation of Landsat imagery were used to extract the glacier boundary in the Nujiang-Salween River Basin(NSRB)around the years 1975,2000,and 2020.The spatiotemporal char...Automated image classification and visual interpretation of Landsat imagery were used to extract the glacier boundary in the Nujiang-Salween River Basin(NSRB)around the years 1975,2000,and 2020.The spatiotemporal characteristics of glacier area changes in the NSRB were determined and the reasons for the spatial heterogeneity in glacier area changes were discussed,based on comparative analyses of temperature and precipitation data from meteorological stations around the NSRB.The results indicate that 1)the total glacier area in the NSRB decreased by 477.78 km^(2)(28.17%)at a rate of-0.62%/a in 1975-2020.Most shrinkage occurred at low and mid altitudes,with the most severe occurring at 5290-5540 m,accounting for 40%of the total shrinkage.Considering other river basins in China,the relative glacier area change rate in the NSRB was similar to that for typical inland river basins in northwest China but lower than that for other transboundary river basins in the southeastern Tibetan Plateau.2)These areal changes in the NSRB presented obvious regional differences.The glaciers in the Hengduan Mountains retreated significantly,followed by those in the Nyainqentanglha Mountains,with relatively low shrinkage observed in the Tanggula Mountains.The number of cold and hot spots indicating areal changes increased after 2000,along with their spatial heterogeneity.3)The glacier shrinkage rate over different time intervals was positively correlated with temperature.Thus,spatial heterogeneity of climate change effects could elucidate differences in the glacier area change rate in different regions of the NSRB.The temperature rise was determined as the primary reason for the significant glacial retreat over the past 45 years.As the significant warming trend continues,the glacier area in the NSRB is likely to shrink further.展开更多
基金supported by the National Natural Science Foundation of China (12072365)the Natural Science Foundation of Hunan Province of China (2020JJ4657)。
文摘It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.
基金National Natural Science Foundation of China,No.42061005,No.41561003Science and Technology Projects of Yunnan Province,No.202101AT070110。
文摘Automated image classification and visual interpretation of Landsat imagery were used to extract the glacier boundary in the Nujiang-Salween River Basin(NSRB)around the years 1975,2000,and 2020.The spatiotemporal characteristics of glacier area changes in the NSRB were determined and the reasons for the spatial heterogeneity in glacier area changes were discussed,based on comparative analyses of temperature and precipitation data from meteorological stations around the NSRB.The results indicate that 1)the total glacier area in the NSRB decreased by 477.78 km^(2)(28.17%)at a rate of-0.62%/a in 1975-2020.Most shrinkage occurred at low and mid altitudes,with the most severe occurring at 5290-5540 m,accounting for 40%of the total shrinkage.Considering other river basins in China,the relative glacier area change rate in the NSRB was similar to that for typical inland river basins in northwest China but lower than that for other transboundary river basins in the southeastern Tibetan Plateau.2)These areal changes in the NSRB presented obvious regional differences.The glaciers in the Hengduan Mountains retreated significantly,followed by those in the Nyainqentanglha Mountains,with relatively low shrinkage observed in the Tanggula Mountains.The number of cold and hot spots indicating areal changes increased after 2000,along with their spatial heterogeneity.3)The glacier shrinkage rate over different time intervals was positively correlated with temperature.Thus,spatial heterogeneity of climate change effects could elucidate differences in the glacier area change rate in different regions of the NSRB.The temperature rise was determined as the primary reason for the significant glacial retreat over the past 45 years.As the significant warming trend continues,the glacier area in the NSRB is likely to shrink further.
