In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by ...In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.展开更多
Seismicity of the Earth （M ≥ 4.5） was compiled from NEIC, IRIS and ISC catalogues and used to compute b-value based on various time windows. It is found that continuous cyclic b-variations occur on both long and sh...Seismicity of the Earth （M ≥ 4.5） was compiled from NEIC, IRIS and ISC catalogues and used to compute b-value based on various time windows. It is found that continuous cyclic b-variations occur on both long and short time scales, the latter being of much higher value and sometimes in excess of 0.7 of the absolute b-value. These variations occur not only yearly or monthly, but also daily. Before the occurrence of large earthquakes, b-values start increasing with variable gradients that are affected by foreshocks. In some cases, the gradient is reduced to zero or to a negative value a few days before the earthquake occurrence. In general, calculated b-values attain maxima 1 day before large earthquakes and minima soon after their occurrence. Both linear regression and maximum likelihood methods give correlatable, but variable results. It is found that an expanding time window technique from a fixed starting point is more effective in the study of b-variations. The calculated b-variations for the whole Earth, its hemispheres, quadrants and the epicentral regions of some large earthquakes are of both local and regional character, which may indicate that in such cases, the geodynamic processes acting within a certain region have a much regional effect within the Earth. The b-variations have long been known to vary with a number of local and regional factors including tectonic stresses. The results reported here indicate that geotectonic stress remains the most significant factor that controls b-variations. It is found that for earthquakes with Mw ≥ 7, an increase of about 0.20 in the b-value implies a stress increase that will result in an earthquake with a magnitude one unit higher.展开更多
Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in curre...Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex tasks.In this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is proposed.In LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of LST2D.Furthermore,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction efficiency.Comprehensive simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of LST2D.The proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.展开更多
The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regio...The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regions and periods vary,and the reasons for this variability are yet to be explained.Thus,in this study,we proposed a new remote sensing ecological vulnerability index by considering moisture,heat,greenness,dryness,land degradation,and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin,China from 2000 to 2022 and its driving mechanisms.The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy,at 86.36%,which indicated a higher applicability in the Yellow River Basin.From 2000 to 2022,the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03,denoting moderate vulnerability level.The intensive vulnerability area was the most widely distributed,which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province.From 2000 to 2022,the ecological vulnerability in the Yellow showed an overall stable trend,while that of the central and eastern regions showed an obvious trend of improvement.The gravity center of ecological vulnerability migrated southwest,indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin.The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index(NDVI)to temperature from 2000 to 2022,and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation,which indicated that the global climate change exerted a more significant impact on regional ecosystems.The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.展开更多
Focusing on the b-value as the research target and under the theoretical framework that the b-value is determined by stress state and medium properties, the variation characteristics of the b-value in the Hetao seismi...Focusing on the b-value as the research target and under the theoretical framework that the b-value is determined by stress state and medium properties, the variation characteristics of the b-value in the Hetao seismic belt are analyzed. Earthquakes with ML≥1. 5,which have occurred in the Hetao seismic belt since 1970 are selected to conduct the quantitative detection of the non-uniform temporal change of Mcusing the EMR method. Based on the actual situation of seismic activity,the lower limit magnitude is set as ML2. 0 to calculate the b-value. The temporal variation of the b-value is calculated and scanned using the least square method. The results show that there is a good corresponding relationship between the temporal variation of the b-value,strong earthquake activity,network distribution and aftershock deletion. We also calculate and scan the spatial variation of the b-value by using maximum likelihood. The results show that the spatial difference is possibly caused by stress state and crustal medium properties. The tectonic dependence of the b-value is obvious. In addition,the sufficient earthquakes samples in each magnitude interval are still a key step to improve the calculation accuracy of the b-value.展开更多
基金Supported by the National Natural Science Foundation of China(No.40675071)~~
文摘In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.
文摘Seismicity of the Earth （M ≥ 4.5） was compiled from NEIC, IRIS and ISC catalogues and used to compute b-value based on various time windows. It is found that continuous cyclic b-variations occur on both long and short time scales, the latter being of much higher value and sometimes in excess of 0.7 of the absolute b-value. These variations occur not only yearly or monthly, but also daily. Before the occurrence of large earthquakes, b-values start increasing with variable gradients that are affected by foreshocks. In some cases, the gradient is reduced to zero or to a negative value a few days before the earthquake occurrence. In general, calculated b-values attain maxima 1 day before large earthquakes and minima soon after their occurrence. Both linear regression and maximum likelihood methods give correlatable, but variable results. It is found that an expanding time window technique from a fixed starting point is more effective in the study of b-variations. The calculated b-variations for the whole Earth, its hemispheres, quadrants and the epicentral regions of some large earthquakes are of both local and regional character, which may indicate that in such cases, the geodynamic processes acting within a certain region have a much regional effect within the Earth. The b-variations have long been known to vary with a number of local and regional factors including tectonic stresses. The results reported here indicate that geotectonic stress remains the most significant factor that controls b-variations. It is found that for earthquakes with Mw ≥ 7, an increase of about 0.20 in the b-value implies a stress increase that will result in an earthquake with a magnitude one unit higher.
基金Joint Funds of the National Natural Science Foundation of China,Grant/Award Number:U21A20518National Natural Science Foundation of China,Grant/Award Numbers:62106279,61903372。
文摘Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex tasks.In this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is proposed.In LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of LST2D.Furthermore,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction efficiency.Comprehensive simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of LST2D.The proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.
基金funded by the National Natural Science Foundation of China(42471329,42101306,42301102)the Natural Science Foundation of Shandong Province(ZR2021MD047)+1 种基金the Scientific Innovation Project for Young Scientists in Shandong Provincial Universities(2022KJ224)the Gansu Youth Science and Technology Fund Program(24JRRA100).
文摘The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regions and periods vary,and the reasons for this variability are yet to be explained.Thus,in this study,we proposed a new remote sensing ecological vulnerability index by considering moisture,heat,greenness,dryness,land degradation,and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin,China from 2000 to 2022 and its driving mechanisms.The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy,at 86.36%,which indicated a higher applicability in the Yellow River Basin.From 2000 to 2022,the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03,denoting moderate vulnerability level.The intensive vulnerability area was the most widely distributed,which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province.From 2000 to 2022,the ecological vulnerability in the Yellow showed an overall stable trend,while that of the central and eastern regions showed an obvious trend of improvement.The gravity center of ecological vulnerability migrated southwest,indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin.The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index(NDVI)to temperature from 2000 to 2022,and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation,which indicated that the global climate change exerted a more significant impact on regional ecosystems.The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.
基金sponsored by the Spark Program of Earthquake Sciences of China Earthquake Administration(XH15010 Y)
文摘Focusing on the b-value as the research target and under the theoretical framework that the b-value is determined by stress state and medium properties, the variation characteristics of the b-value in the Hetao seismic belt are analyzed. Earthquakes with ML≥1. 5,which have occurred in the Hetao seismic belt since 1970 are selected to conduct the quantitative detection of the non-uniform temporal change of Mcusing the EMR method. Based on the actual situation of seismic activity,the lower limit magnitude is set as ML2. 0 to calculate the b-value. The temporal variation of the b-value is calculated and scanned using the least square method. The results show that there is a good corresponding relationship between the temporal variation of the b-value,strong earthquake activity,network distribution and aftershock deletion. We also calculate and scan the spatial variation of the b-value by using maximum likelihood. The results show that the spatial difference is possibly caused by stress state and crustal medium properties. The tectonic dependence of the b-value is obvious. In addition,the sufficient earthquakes samples in each magnitude interval are still a key step to improve the calculation accuracy of the b-value.
