Trends of road traffic mortality in Tehran city during 2012-2021 by Amir Kavousi, Khaled Rahmani, Ali Moradi, Fatemeh Darabi, Mohammad Razeghi

“…Over the years, a pronounced reduction in fatalities has been observed compared to 2012 figures. …”
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The Study of Spatial Heterogeneity and Interregional Relations in the Processes of Attracting Banking Capital to the Russian Economy by I. V. Naumov, S. S. Krasnykh

“…The purpose of the research is to assess the dynamics of changes in spatial heterogeneity in the processes of attracting banking capital in the Russian economy and to model the system of interregional relationships in these processes. …”
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Connectome-based prediction of functional impairment in experimental stroke models. by Oliver Schmitt, Peter Eipert, Yonggang Wang, Atsushi Kanoke, Gratianne Rabiller, Jialing Liu

“…Dynamic modeling with the weighted bilateral connectome detected changes in signal propagation in the remote hippocampus in all 3 stroke types, predicting the extent of hippocampal hypoactivation and impairment in spatial learning and memory function. …”
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Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…In this paper, we introduce a novel deep learning-based model, adaptive-GCNLSTM (Ada-GCNLSTM). Specifically, in the spatial feature extraction module, we enhance the model's ability to capture crime spatial distributions by leveraging graph convolutional networks to model spatial dependencies in conjunction with the maximum mean discrepancy to extract the universal features of crime data. …”
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A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…The random forest (RF) model is widely used in population spatialization studies. …”
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The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system. by Franco M Neri, Anne Bates, Winnie S Füchtbauer, Francisco J Pérez-Reche, Sergei N Taraskin, Wilfred Otten, Douglas J Bailey, Christopher A Gilligan

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EpiGeoPop: a tool for developing spatially accurate country-level epidemiological models by Lara Herriott, Henriette L. Capel, Isaac Ellmen, Nathan Schofield, Jiayuan Zhu, Ben Lambert, David Gavaghan, Ioana Bouros, Richard Creswell, Kit Gallagher

“…Agent-based models (ABMs) have emerged as a valuable tool, capturing population heterogeneity and spatial effects, particularly when assessing potential intervention strategies. …”
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Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool. by Rachel L Pullan, Peter W Gething, Jennifer L Smith, Charles S Mwandawiro, Hugh J W Sturrock, Caroline W Gitonga, Simon I Hay, Simon Brooker

“…The model estimated that a total of 2.8 million school-age children live in districts which warrant mass treatment.…”
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Lightweight pose estimation spatial-temporal enhanced graph convolutional model for miner behavior recognition by WANG Jianfang, DUAN Siyuan, PAN Hongguang, JING Ningbo

“…MEST-GCN improved upon the spatial-temporal graph convolutional network (ST-GCN) by removing redundant layers to simplify the model structure and reduce the number of parameters. …”
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Impact of Urban Spatial Compactness on Carbon Emissions: Heterogeneity at the County Level in the Beijing–Tianjin–Hebei Area, China by Muhan Li, Minghao Zuo, Saiyi Chen, Shuang Tang, Tian Chen, Jia Liu

“…However, the potential of and variations in spatial compactness in county-level carbon reduction have been largely overlooked. …”
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Traffic flow prediction based on spatiotemporal encoder-decoder model. by Yuanming Ding, Wei Zhao, Lin Song, Chen Jiang, Yunrui Tao

“…Specifically, on the PeMSD8 dataset, the model achieves reductions in MAE, RMSE, and SMAPE by 7.9%, 2.1%, and 16.9%, respectively, compared to the AMRGCN model for 1-hour predictions. …”
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Liner Wear Prediction Using Bayesian Regression Models and Clustering by Jacob Van Den Broek, Melinda Hodkiewicz, Adriano Polpo

“…Notably, Model 2 predicts remaining useful life within 95% credible intervals and identifies anomalous sensor performance. …”
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Building Fire Location Predictions Based on FDS and Hybrid Modelling by Yanxi Cao, Hongyan Ma, Shun Wang, Yingda Zhang

“…With the goal of addressing the difficulty of rapidly identifying the source of fire in commercial buildings, this study builds a numerical fire model based on the fire dynamics simulator (FDS) and combines it with a hybrid model to predict the location of a fire source. …”
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Evaluation and Optimization of Prediction Models for Crop Yield in Plant Factory by Yaoqi Peng, Yudong Zheng, Zengwei Zheng, Yong He

“…By incorporating crop yield data, a comparative analysis of 28 prediction models was performed, assessing performance metrics such as MSE, RMSE, MAE, MAPE, R², prediction speed, training time, and model size. …”
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Machine learning models for predicting spatiotemporal dynamics of groundwater recharge by Azeddine Elhassouny

“…A comparison of spatiotemporal prediction models' estimates of groundwater recharge in Morocco revealed AdaBoost and RF were the more accurate methods for temporal and spatial prediction, with RMSE values of 10.9712 mm/month and 5.0089 mm/month, respectively. …”
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Probabilistic Uncertainty Consideration in Regionalization and Prediction of Groundwater Nitrate Concentration by Divas Karimanzira

“…In this study, we extend our previous work on a two-dimensional convolutional neural network (2DCNN) for spatial prediction of groundwater nitrate, focusing on improving uncertainty quantification. …”
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Exploration of Carbon Emission Reduction Pathways for Urban Residential Buildings at the Provincial Level: A Case Study of Jiangsu Province by Jian Xu, Tao Lei, Milun Yang, Huixuan Xiang, Ronge Miao, Huan Zhou, Ruiqu Ma, Wenlei Ding, Genyu Xu

“…This study examines Jiangsu Province in eastern China—a economic hub with north-south development gradients—to develop an integrated framework for differentiated carbon reduction pathways. The methodology combines spatial autocorrelation analysis, logarithmic mean Divisia index (LMDI) decomposition, system dynamics modeling, and Tapio decoupling analysis to examine urban residential building emissions across three regions from 2016–2022. …”
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Factors influencing docked bike-sharing usage in the City of Kigali, Rwanda by Jean Marie Vianney Ntamwiza, Hannibal Bwire

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Study on Spatial and Temporal Evolution of Carbon Stock in East Coastal Area of Zhejiang Based on InVEST and GIS Modeling by Chen Fang, Zhiyu Wang

“…Global climate change, driven by increasing carbon emissions, poses a significant challenge to sustainable development, yet regional studies on carbon stock dynamics in rapidly urbanizing coastal areas remain limited. Utilizing the InVEST model and GIS spatial analysis methods, this research examines the spatiotemporal dynamics of carbon stock in the eastern coastal regions of Zhejiang from 2000 to 2020. …”
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Effects of Coverage Area Treatment, Spatial Analysis Unit, and Regression Model on the Results of Station-Level Demand Modeling of Urban Rail Transit by Hongtai Yang, Chaojing Li, Xuan Li, Jinghai Huo, Yi Wen, Emma G. P. Sexton, Yugang Liu

“…Direct ridership models can predict station-level urban rail transit ridership. …”
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