Journal of Geographical Sciences - Population migration, especially population inflow from epidemic areas, is a key source of the risk related to the coronavirus disease 2019 (COVID-19) epidemic.... 相似文献
ABSTRACTThe spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns. 相似文献
Mineral potential prediction is a process of establishing a statistical model that describes the relationship between evidence variables and mineral occurrences. In this study, evidence variables were constructed from geological, remote sensing, and geochemical data collected from the Lalingzaohuo district, Qinghai Province, China. Based on these evidence variables, a conjugate gradient logistic regression (CG-LR) model was established to predict exploration targets in the study area. The receiver operating characteristic (ROC) and prediction–area (P-A) curves were used to evaluate the effectiveness of the CG-LR model in mineral potential mapping. The difference between the vertical and horizontal coordinates of each point on the ROC curve was used to determine the optimal threshold for classifying the exploration targets. The optimal threshold corresponds to the point on the ROC curve where the difference between the vertical coordinate and the horizontal coordinate is the largest. In exploration target prediction in the study area, the CG algorithm was used to optimize iteratively the LR coefficients, and the prediction effectiveness was tested for different epochs. With increasing iterations, the prediction performance of the model becomes increasingly better. After 60 iterations, the LR model becomes stable and has the best performance in exploration target prediction. At this point, the exploration targets predicted by the CG-LR model occupy 14.39% of the study area and contain 93% of the known mineral deposits. The exploration targets predicted by the model are consistent with the metallogenic geological characteristics of the study area. Therefore, the CG-LR model can effectively integrate geological, remote sensing, and geochemical data for the study area to predict targets for mineral exploration.
The Antarctic krill(Euphausia superba) is a key species in the Southern Ocean ecosystem and an important link in the food web of the Antarctic ecosystem. The trophic information for this species during the transition from the austral fall to the winter is important to understand its poorly known overwintering mechanisms. However, the few studies on the topic differ in their results, in terms of both spatial and temporal variables. We investigated the size dependence and monthly and regional variation in δ~(13) C and δ~(15) N values of adult krill in the Antarctic Peninsula, in the austral fall(April to May) and the early winter(June). We aimed to examine the trophic variations of krill occurred during this period, and the relationship between krill and their feeding environment in the Antarctic marine ecosystem. The following results were obtained:(1) no significant relationship was observed between size and the δ13 C value of krill, but the δ15 N value of krill presented a remarkable association with size;(2)the δ13 C values of krill increased during the austral fall, but no remarkable variation existed at the onset of winter,and the δ15 N values were not significant different during this period;(3) mean δ15 N values of krill differed significantly between the Bransfield Strait and the South Shetland Islands. Our data imply that adult krill present size-, season-, and region-dependent trophic variation during the transition from austral fall to early winter in the Antarctic Peninsula. 相似文献
Grain price volatility during historical periods is regarded as an important indicator of the impact of climate change on economic system, as well as a key link to adjust food security and social stability. The present study used the wheat prices in Baoding Prefecture, China, during 1736–1850 to explore connections between climatic transition and grain price anomalies in the North China Plain. The main findings were as follows:(1) The grain price change showed an apparent correspondence with climatic transition. The period 1781–1820 was a transition phase, with more extremes and decreased precipitations when the climate shifted from a warm phase to a cold one. Corresponding with the climatic transition, the grain price during 1781–1820 was characterized by that the mean of the original grain price series was significantly higher(lower) than the previous(later)phase, and the variance and anomaly amplitude of the detrended grain price series was the highest during 1736–1850.(2) The correspondence between grain price extremes and drought events occurred in phases. Five grain price extremes occurred following drought events during 1781–1810, while extreme droughts were the direct cause of the grain price spike during 1811–1820.(3) Social stability affected by climate change also played an important role in the grain price spike between 1811 and 1820. Paralleling the pathway of "precipitation-grain production-grain price", climate change could have an impact on grain price via the pathway of "precipitation-grain production-grain price-famine-uprising-grain price", as shown during the Tianli Uprising in 1813. These findings could contribute to an improved understanding of the interaction between climate change and human society during the historical period. 相似文献