Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer
SensorsWeather prediction is of great significance for human daily production activities, global extreme climate prediction, and environmental protection of the Earth.
Ruowu Wu +3 more
doaj +2 more sources
PMSTD-Net: A Neural Prediction Network for Perceiving Multi-Scale Spatiotemporal Dynamics
SensorsWith the continuous advancement of sensing technology, applying large amounts of sensor data to practical prediction processes using artificial intelligence methods has become a developmental direction. In sensing images and remote sensing meteorological
Feng Gao, Sen Li, Yuankang Ye, Chang Liu
doaj +2 more sources
Spatiotemporal Soil Moisture Prediction Using a Causal-Guided Deep Learning Model
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe spatiotemporal prediction of RZSM refers to the process of estimating its future spatial distribution and temporal variations using predictive models.
Tingtao Wu +8 more
doaj +2 more sources
Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables [PDF]
, 2022 Crop yield forecasting is critical for enhancing food security and ensuring an appropriate food supply. It is critical to complete this activity with high precision at the regional and national levels to facilitate speedy decision-making.
Ahmed, A. A. Masrur +13 more
core +1 more source
UCTB: Spatiotemporal Crowd Flow Prediction Toolbox
, 2022 Spatiotemporal crowd flow prediction is one of the key technologies in smart cities. There are mainly two major shortcomings that plague researchers and developers. Firstly, crowd flow is affected by complex factors and previous studies have summarized a
Chen, Liyue, Wang, Leye, Chai, Di
core +1 more source
Hand, foot and mouth disease: spatiotemporal transmission and climate [PDF]
, 2011 BACKGROUND: The Hand-Foot-Mouth Disease (HFMD) is the most common infectious disease in China, its total incidence being around 500,000~1,000,000 cases per year. The composite space-time disease variation is the result of underlining attribute mechanisms
Zhong-Jie Li +20 more
core +1 more source
Topology prediction for opportunistic network based on spatiotemporal convolution [PDF]
, 2023 The high dynamics of opportunistic network topology leads to the challenges of topology prediction.The existing research mainly focuses on the long-term spatiotemporal dependence of networks, ignoring the short-term spatiotemporal features.A topology ...
Jian SHU +3 more
core +1 more source
Optimal spatiotemporal prediction of karstwater levels [PDF]
, 1999 In many fields of applied statistics samples from several locations in an investigation area are taken repeatedly over time. Especially in environmental monitoring the chemical and physics conditions in water, air and soil are measured using fixed and ...
Berke, O. (Medizinische Hochschule Hannover (Germany). Inst. fuer Biometrie und Epidemiologie) +1 more
core +2 more sources
GridTuner: Reinvestigate Grid Size Selection for Spatiotemporal Prediction Models
, 2022 With the development of traffic prediction technology, spatiotemporal prediction models have attracted more and more attention from academia communities and industry. However, most existing researches focus on reducing model's prediction error but ignore
Lei Chen +9 more
core +1 more source
Spatiotemporal Prediction of Theft Risk with Deep Inception-Residual Networks
, 2021 Spatiotemporal prediction of crime is crucial for public safety and smart cities operation. As crime incidents are distributed sparsely across space and time, existing deep-learning methods constrained by coarse spatial scale offer only limited values in
Qiong Peng, Lian Duan, Xinyue Ye
core +2 more sources