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STVMamba: precipitation nowcasting with spatiotemporal prediction model
Published 2025-07-01“…The Spatial-Temporal Vision Mamba (STVMamba) is proposed, a novel spatiotemporal prediction model specifically designed for precipitation nowcasting. …”
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282
Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting
Published 2025-01-01“…Rapidly accumulating, large-scale and long-term meteorological data provide unprecedented opportunities for data-driven meteorological models and fine-grained numerical weather prediction. …”
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283
Integrating Higher Education Strategies into Urban Cluster Development: Spatial Agglomeration Analysis of China’s Key Regions
Published 2025-06-01“…Using dynamic panel regression and spatial econometric models, the results show that HEA yields significant local and spatial spillover benefits, particularly in core cities that facilitate knowledge diffusion and resource sharing. …”
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284
Spatial Weight Matrix Comparison of SAR-X Model using Casetti Approach
Published 2024-05-01“…The Spatial Autoregressive Exogenous (SAR-X) model with the Casetti approach is used to describe the influence of location and exogenous variables in the description and prediction of spatial observations, namely, people's habits and behavior towards culture in Java Island. …”
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285
A multimodal model for protein function prediction
Published 2025-03-01“…Protein structure provides richer spatial and functional insights, which can significantly improve prediction accuracy. …”
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286
Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs)
Published 2025-04-01“…A stepwise procedure was followed to determine the model with the optimal set of covariates. A leave-one-out cross-validation method was used to estimate the prediction error. …”
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287
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Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer’s Disease Detection
Published 2025-01-01“…These features are processed through a dual-stream DL model, where each stream captures complementary spatial features. …”
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289
Unsupervised feature correlation-based spatial stratification for local context-aware modelling
Published 2025-12-01“…Context-aware modelling improves the accuracy of spatial inferences through using local environmental conditions, spatial dependency, and heterogeneity. …”
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290
Transient Stability Assessment Model With Sample Selection Method Based on Spatial Distribution
Published 2024-01-01“…Sample selection aims to optimize the training set to speed up the training process while improving the preference of the TSA model. The typical samples which can accurately express the spatial distribution of the raw dataset are selected by the proposed method. …”
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291
Drivers of Future Indian Ocean Warming and Its Spatial Pattern in CMIP Models
Published 2025-04-01“…Abstract Coupled Model Intercomparison Project phases 5 and 6 (CMIP5/6) projections display substantial inter‐model diversity in the future tropical Indian Ocean warming magnitude and spatial pattern. …”
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292
Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality
Published 2012-01-01Get full text
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293
Spatial distribution model of anoa, Bubalus spp., in Tanjung Peropa Wildlife Reserve
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294
Temporal and spatial pattern analysis and forecasting of methane: Satellite image processing
Published 2025-11-01“…Atmospheric dispersion modeling is a critical tool in environmental research, offering insights into spatial and temporal patterns of pollutants. …”
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295
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Leveraging Spatial and Temporal Data to Predict Heavy Freight Vehicle Traffic Flow on Rural Road Network
Published 2025-01-01“…The extreme gradient boosting (XGBoost) model surpasses the time-series model in predictive accuracy, yielding average R-squared values of 84.7% and 85.8% on the test data for trucks and tractor-trailers, respectively. …”
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Spatial Prediction of Soil Total Phosphorus in a Karst Area: Comparing GWR and Residual-Centered Kriging
Published 2024-12-01“…GWRK also achieved the highest R<sup>2</sup> (0.67), demonstrating robust predictive capability. MM_OK and MC_OK models performed well and showed smoother spatial transitions, while the OK model displayed the lowest predictive accuracy (62%). …”
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299
Modelling the soil microclimate: does the spatial or temporal resolution of input parameters matter?
Published 2016-01-01“…<div class="WordSection1"><p>The urgency of predicting future impacts of environmental change on vulnerable populations is advancing the development of spatially explicit habitat models. …”
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