Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…In order to better apply the stacking model to the prediction of new infectious diseases, we applied the prediction model based on the COVID-19 dataset to the prediction of the number of AIDS and pulmonary tuberculosis (PTB) cases, and verified the wide applicability of our model in the prediction of infectious diseases.…”
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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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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

“…In this framework, cells are modeled as nodes in a directed graph, with dynamic connections representing variations in signal phases, thereby embedding spatial relationships and signal information within dynamic graphs. …”
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Predict the carcinogenicity of compounds with SGCN by Wei Ruobing, He Jiafeng, Qiu Xiaofang, Liu Qi

“…In this paper, 341 kinds of experimental data were obtained, and the spatial atom feature combined with the spatial graph convolutional network(SGCN) was used to establish a model that could predict the carcinogenicity of compounds. …”
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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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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 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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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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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

“…A small number of direct measurements or their extremely uneven distribution leads to significant model errors. This article explores the possibility of using multidimensional approximation and regression splines, both considering spatially referenced direct observation data and using well log curves statistically linked to the modeled variables. …”
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OceanLSTM: xLSTM with spatial attention for salt spray formation and migration prediction in marine hot-humid environments by Chuan Chen, Ganxin Jie, Jun Wang, Shouhe Wang, Xiaonong Xu

Subjects: “…salt spray prediction…”
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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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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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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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ED-SA-ConvLSTM: A Novel Spatiotemporal Prediction Model and Its Application in Ionospheric TEC Prediction by Yalan Li, Haiming Deng, Jian Xiao, Bin Li, Tao Han, Jianquan Huang, Haijun Liu

“…Existing work based on Convolutional Long Short-Term Memory (ConvLSTM) primarily relies on convolutional operations for spatial feature extraction, which are effective at capturing local spatial correlations, but struggle to model long-range dependencies, limiting their predictive performance. …”
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Terrain Simplification Algorithm in Radio Wave Propagation Prediction by Dan Shi, Zhen Zhang, Fengshuo Wei, Cheng Lian

“…The spatial visibility algorithm and the probability-based power propagation model can be applied to the complex electromagnetic environment to analyze the influence of terrain simplification on prediction accuracy. …”
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Modeling the spatial distribution of anthrax in southern Kenya. by Fredrick Tom Otieno, John Gachohi, Peter Gikuma-Njuru, Patrick Kariuki, Harry Oyas, Samuel A Canfield, Jason K Blackburn, M Kariuki Njenga, Bernard Bett

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