Testing the Applicability and Transferability of Data-Driven Geospatial Models for Predicting Soil Erosion in Vineyards by Tünde Takáts, László Pásztor, Mátyás Árvai, Gáspár Albert, János Mészáros

“…Predictions used spatially exhaustive, auxiliary, and environmental covariables. …”
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Conditional logistic individual-level models of spatial infectious disease dynamics by Tahmina Akter, Rob Deardon

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Prediction of the Spatial Distribution of Petrophysical Properties of Sediment Formations Using Multidimensional Splines by V. V. Lapkovsky, V. A. Kontorovich, K. I. Kanakova, S. E. Ponomareva, B. V. Lunev

“…The results can be computed for individual wells as for inter-well space, allowing for the creation of geological cross-sections of predicted properties and 3D models of their distribution. …”
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An AI-based gravitrap surveillance for spatial interaction analysis in predicting aedes risk by Hsiang-Yu Yuan, Pei-Sheng Lin, Wei-Liang Liu, Tzai-Hung Wen, Yu-Chun Lu, Chun-Hong Chen, Li‑Wei Chen

“…Information from neighboring villages is incorporated into the model to enhance precision of risk prediction. Results The proposed AI gravitrap index integrates the auto-Markov and disease mapping models to enhance sensitivity in risk prediction for Aedes densities. …”
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Applying Machine Learning Algorithms for Spatial Modeling of Flood Susceptibility Prediction over São Paulo Sub-Region by Temitope Seun Oluwadare, Marina Pannunzio Ribeiro, Dongmei Chen, Masoud Babadi Ataabadi, Saba Hosseini Tabesh, Abiodun Esau Daomi

Subjects: “…flood spatial modeling…”
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Spatial modeling for predicting and identifying levels of climate-related disease hazards in Iraq using (GIS) Kirkuk as a model by Abdlwahd Jamel Alqdori Areej

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Integrated framework for assessment and spatial prediction of humus layer properties of forest soils by Felix Thomas, Carina Becker, Rainer Petzold, Karsten Schmidt, Thomas Scholten, Ulrike Werban

“…We tested the developed framework in a case study on a forest site in Saxony, investigating C/N ratio, pH value, cation exchange capacity and base saturation. Random Forest model calibration for spatial prediction achieved R2 > 0.9 for all investigated humus layer properties. …”
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A Predictive Spatial Model to Quantify the Risk of Air-Travel-Associated Dengue Importation into the United States and Europe by Lauren M. Gardner, David Fajardo, S. Travis Waller, Ophelia Wang, Sahotra Sarkar

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Modeling the Spatial Distribution of Wildfire Risk in Chile Under Current and Future Climate Scenarios by John Gajardo, Marco Yáñez, Robert Padilla, Sergio Espinoza, Marcos Carrasco-Benavides

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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…In comparative analyses, the proposed network significantly outperforms prevailing trajectory prediction models across multiple dimensions. In this paper, we propose a new deep learning network, and apply it to the real-world engineering challenge of spatial target trajectory prediction in the air traffic management domain.…”
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Vit-Traj: A Spatial–Temporal Coupling Vehicle Trajectory Prediction Model Based on Vision Transformer by Rongjun Cheng, Xudong An, Yuanzi Xu

“…In recent years, data-driven vehicle trajectory prediction models have become a significant research focus, and various spatial–temporal neural network models, based on spatial–temporal data, have been proposed. …”
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Spatial-temporal deep learning model based on Similarity Principle for dock shared bicycles ridership prediction by Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang

“…The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. …”
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Investigating the Impact of Climate Change on the Effective Indicators in Desertification and Predicting its Spatial Changes by Azam Sadat Hosseini Khezr Abad, Abassali Vali, Amirhossein Halabian, Mohammad Hossein Mokhtari, Seyyed Ali Mousavi

“…Excessive dryness of arid regions has increased the intensity and spread of desertification. Investigating spatial and temporal patterns of desertification caused by climate change in the northwest of Yazd province using the Iranian model of desertification potential assessment (IMDPA) is one of the main objectives of this research. …”
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Spatial-temporal load prediction of electric bus charging station based on S2TAT by Guangnian Xiao, Hailin Tong, Yaqing Shu, Anning Ni

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Modelling and Using Spatial Effects in Nationwide Historical Data Improve Genomic Prediction of Rice Heading Date in Japan by Shoji Taniguchi, Takeshi Hayashi, Hiroshi Nakagawa, Kei Matsushita, Hiromi Kajiya-Kanegae, Jun-Ichi Yonemaru, Akitoshi Goto

“…To improve the prediction accuracy of models using historical data, we incorporated a spatial model to account for spatial structures among field stations, in addition to conventional genomic prediction models. …”
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Development of a river dissolved oxygen prediction model integrating spatial effects and multiple deep learning algorithm by Yubo Zhao, Mo Chen

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Spatial Modeling of Auto Insurance Loss Metrics to Uncover Impact of COVID-19 Pandemic by Shengkun Xie, Jin Zhang

Subjects: “…spatial model…”
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Modeling Spatial and Temporal Changes in Land-Uses and Land Cover of the Urmia Lake Basin Applying Cellular Automata and Markov Chain by Hadi Eskandari Damaneh, Hamid Gholami, Hassan Khosravi, Rasoul Mahdavi Najafabadi, Asadollah Khoorani, Gimmy Li

“…After the integrated CA-Markov approach assessed the model, the land-use maps were predicted for the years 2028 and 2038. …”
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Machine learning based risk analysis and predictive modeling of structure fire related casualties by Andres Schmidt, Eric Gemmil, Russ Hoskins

“…Our results show that the age of victims, fire service response times, and availability of working smoke or fire detectors were among the most important parameters for predicting fatal outcomes of structure fires. Furthermore, a predictive Bayesian regularized neural network ensemble classifier was developed to model the severity of casualties and project a spatial risk classification on the census block level. …”
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Urban Signalized Intersection Traffic State Prediction: A Spatial–Temporal Graph Model Integrating the Cell Transmission Model and Transformer by Anran Li, Zhenlin Xu, Wenhao Li, Yanyan Chen, Yuyan Pan

“…Temporal embeddings derived from time attributes are integrated with these graphs to generate comprehensive spatial–temporal representations. Utilizing an encoder–decoder architecture, CeT captures dependencies and correlations from past cell states to predict future traffic conditions. …”
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