Modeling suspected malaria cases in Papua province with second order Besag-York-Mollie 2 spatial regression by Kirana Azzahra, Ro'fah Nur Rachmawati, Muhamad Syazali

“…Based on these results, it is concluded that the INLA approach with second-order spatial modelling is effective for analysing and predicting suspected malaria cases in Papua. …”
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Assessing sensitivity of stream migration at Foothill Areas: Hydrological modeling and spatial analysis of the Red Sea coastal stream by Ahmed Foda, Ahmed Abdelhalim, Mustafa Elkhedr

“…An integrated methodology combining hydrological modeling using HEC-RAS 2D, GIS-based spatial analysis, and sediment transport simulation was implemented to quantify channel movement and assess potential scour locations. …”
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Spatial modeling of snow water equivalent in the high atlas mountains via a lumped process-based approach by Siham Acharki, Abdelghani Boudhar, Ayoub Bouihrouchane, Mostafa Bousbaa, Ismail Karaoui, Haytam Elyoussfi, Bouchra Bargam, El Mahdi El Khalki, Abdessamad Hadri, Abdelghani Chehbouni

“…Thus, accurate SWE assessment is essential for predicting the spatial distribution of snowpack and its temporal contributions to downstream outflow, particularly in semi-arid snow-fed basins like Morocco’s High Atlas regions. …”
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Reduction in the potential distribution of bee species in low latitudes under different climate change scenarios: conservation implications by Xinggang Tang, Xinggang Tang, Zheng He, Zheng He, Yue Deng, Yue Deng, Yingdan Yuan, Kaiming Zeng, Kaiming Zeng

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Dynamic spatiotemporal graph network for traffic accident risk prediction by Pengcheng Zhang, Wen Yi, Yongze Song, Penggao Yan, Peng Wu, Ammar Shemery, Keith Hampson, Albert P. C. Chan

“…The dynamic learning of spatial correlations, combined with the integration of road characteristics and contextual variables, significantly enhances the accuracy of traffic accident predictions. …”
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Linear attention based spatiotemporal multi graph GCN for traffic flow prediction by Yanping Zhang, Wenjin Xu, Benjiang Ma, Dan Zhang, Fanli Zeng, Jiayu Yao, Hongning Yang, Zhenzhen Du

“…This study introduces the Linear Attention Based Spatial-Temporal Multi-Graph Convolutional Neural Network (LASTGCN), a novel deep learning model tailored for traffic flow prediction. …”
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Spatial Change of Dominant Baltic Sea Demersal Fish Across Two Decades by Liam MacNeil, Frane Madiraca, Saskia Otto, Marco Scotti

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Reviewing the complexity of endogenous technological learning for energy system modeling by Johannes Behrens, Elisabeth Zeyen, Maximilian Hoffmann, Detlef Stolten, Jann M. Weinand

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Research on Spatial Heterogeneity, Impact Mechanism, and Carbon Peak Prediction of Carbon Emissions in the Yangtze River Delta Urban Agglomeration by Pin Chen, Xiyue Wang, Zexia Yang, Changfeng Shi

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Spatial prediction and visualization of PM2.5 susceptibility using machine learning optimization in a virtual reality environment by Seyed Vahid Razavi-Termeh, Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, X. Angela Yao, Soo-Mi Choi

“…The evaluation results of the VR systems from the Virtual Reality Neuroscience Questionnaire (VRNQ) and System Usability Scale (SUS) for spatial visualization showed that they had high graphics capabilities and equipment for the spatial prediction of PM2.5.…”
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A New Prediction Model of Dam Deformation and Successful Application by Shuangping Li, Bin Zhang, Meng Yang, Senlin Li, Zuqiang Liu

“…In view of the poor accuracy of the monitoring data, which reflect the overall deformation response in the current dam monitoring practices, this paper proposes an innovative solution of ensemble empirical mode decomposition and a wavelet noise reduction method. A high-precision prediction model considering spatial correlation is constructed. …”
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Application of Radionuclides Migration Software(MNS) in Radionuclides Diffusion Modeling by Yao LI, Rui-hao LI, Duo ZHOU, Xi CHEN, Yu-wei XU, Bo WANG

“…Pre-processing involves the construction of spatial models and parameter assignment, such as porosity, mineral density, radionuclide diffusion and migration parameters, and water flow velocity. …”
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Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning by Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist

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Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models. by Michael J Tildesley, Sadie J Ryan

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A Combined Model for Simulating the Spatial Dynamics of Epidemic Spread: Integrating Stochastic Compartmentalization and Cellular Automata Approach by Murad Bashabsheh

“…The model presented in this paper is designed to simulate the spatial distribution of diseases in a spatially structured population. …”
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Predictive Deep Learning for High‐Dimensional Inverse Modeling of Hydraulic Tomography in Gaussian and Non‐Gaussian Fields by Quan Guo, Ming Liu, Jian Luo

“…In this work, we develop a novel method called HT‐INV‐NN, which combines dimensionality reduction techniques with a predictive deep learning (DL) model to estimate high‐dimensional Gaussian and non‐Gaussian channel fields. …”
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A Hybrid Spatial–Temporal Deep Learning Method for Metro Tunnel Displacement Prediction Under “Dual Carbon” Background by Jianyong Chai, Limin Jia, Jianfeng Liu, Enguang Hou, Zhe Chen

“…The model leverages the strengths of GCNs in capturing spatial correlations and LSTM networks in processing temporal dynamics, offering a robust framework for accurate displacement prediction. …”
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A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes by Himan Shahabi, Ataollah Shirzadi, Alicja Ustrzycka, Natalia Piotrowska, Janusz Filipiak, Marzieh Hajizadeh Tahan

“…For the first time, this model is used to predict the spatial prediction of a stable isotope in Polish lakes. …”
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Value of MRI radiomics based on intratumoral and peritumoral heterogeneity in predicting spatial patterns of locally recurrent high-grade gliomas by WANG Hanwei, ZENG Linlan, ZHAO Mimi

“… ‍Objective‍　‍To establish and validate a multimodal MRI radiomics model based on intratumoral and peritumoral heterogeneity for prediction of spatial pattern of locally recurrent high-grade gliomas (HGGs). …”
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Spatial-Temporal Distribution Prediction of Charging Load of Electric Truck Cluster Considering Battery Loss Under Path Planning by CUI Jinghao, ZHANG Yi, ZHANG Zhichao, YU Yang

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