Results 11 to 20 of about 3,246,502 (304)

Analyzing the Spatiotemporal Uncertainty in Urbanization Predictions [PDF]

Remote Sensing, 2021
With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make ...
Jairo Alejandro Gomez, ChengHe Guan, Pratyush Tripathy, Juan Carlos Duque, Santiago Passos, Michael Keith, Jialin Liu   +6 more
openaire   +2 more sources

SwinLSTM: Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM [PDF]

IEEE International Conference on Computer Vision, 2023
Integrating CNNs and RNNs to capture spatiotemporal dependencies is a prevalent strategy for spatiotemporal prediction tasks. However, the property of CNNs to learn local spatial information decreases their efficiency in capturing spatiotemporal ...
Song Tang, Chuang Li, Pufen Zhang, R. Tang   +3 more
semanticscholar   +1 more source

KeyMemoryRNN: A Flexible Prediction Framework for Spatiotemporal Prediction Networks [PDF]

IEEE Access, 2021
Most previous recurrent neural networks for spatiotemporal prediction have difficulty in learning the long-term spatiotemporal correlations and capturing skip-frame correlations. The reason is that the recurrent neural networks update the memory states only using information from the previous time step node and the networks tend to suffer from gradient
Shengchun Wang, Xiang Lin, Huijie Zhu
openaire   +2 more sources

GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems

Global Energy Interconnection, 2022
Owing to the expansion of the grid interconnection scale, the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.
Dengyi Huang, Hao Liu, Tianshu Bi, Qixun Yang   +3 more
doaj   +1 more source

Spatial and temporal characteristics analysis and prediction model of PM2.5 concentration based on SpatioTemporal-Informer model.

PLoS ONE, 2023
The primary cause of hazy weather is PM2.5, and forecasting PM2.5 concentrations can aid in managing and preventing hazy weather. This paper proposes a novel spatiotemporal prediction model called SpatioTemporal-Informer (ST-Informer) in response to the ...
Zhanfei Ma, Wenli Luo, Jing Jiang, Bisheng Wang, Ziyuan Ma, Jixiang Lin, Dongxiang Liu   +6 more
doaj   +1 more source

Spatiotemporal Signatures of Lexical–Semantic Prediction [PDF]

Cerebral Cortex, 2014
Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate ...
Lau, E., Weber, K., Gramfort, A., Hämäläinen, M., Kuperberg, G.   +4 more
openaire   +3 more sources

Spatiotemporal Transformer for Stock Movement Prediction

CoRR, 2023
Financial markets are an intriguing place that offer investors the potential to gain large profits if timed correctly. Unfortunately, the dynamic, non-linear nature of financial markets makes it extremely hard to predict future price movements. Within the US stock exchange, there are a countless number of factors that play a role in the price of a ...
Daniel Boyle, Jugal Kalita
openaire   +2 more sources

UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction [PDF]

Neural Information Processing Systems, 2023
Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the development and operation of the smart city. As an emerging building block, multi-sourced urban data are usually integrated as urban knowledge graphs (UrbanKGs) to provide ...
Yansong NING, Hao Liu, Hao Wang, Zhenyu Zeng, H. Xiong   +4 more
semanticscholar   +1 more source

A Novel Multi-Input Multi-Output Recurrent Neural Network Based on Multimodal Fusion and Spatiotemporal Prediction for 0–4 Hour Precipitation Nowcasting

Atmosphere, 2021
Multi-source meteorological data can reflect the development process of single meteorological elements from different angles. Making full use of multi-source meteorological data is an effective method to improve the performance of weather nowcasting. For
Fuhan Zhang, Xiaodong Wang, Jiping Guan
doaj   +1 more source

Analysis of the future trends of typical mountain glacier movements along the Sichuan-Tibet Railway based on ConvGRU network

International Journal of Digital Earth, 2023
The anomalous movements of glaciers cause disasters, such as debris flows and landslides. It is very important to assess the glacier movements and their future trends. Glacier velocity refers to movement process. The current research aims to analyse past
Yali Zhang, Lifeng Zhang, Yi He, Sheng Yao, Wang Yang, Shengpeng Cao, Qiang Sun   +6 more
doaj   +1 more source