Predictive modeling of building energy consumption and thermal comfort for decarbonization in construction and retrofitting by Sameer Algburi, Aymen Mohammed, Ibrahim Abdullah, Talib Munshid Hanoon, Hassan Falah Fakhruldeen, Otabek Mukhitdinov, Feryal Ibrahim Jabbar, Qusay Hassan, Ali Khudhair, David Kato

“…This study introduces an integrated predictive modeling framework for assessing building energy consumption and indoor thermal comfort, with a focus on supporting decarbonization efforts in both new construction and retrofit scenarios. …”
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ReScConv-xLSTM: An improved xLSTM model with spatiotemporal feature extraction capability for remaining useful life prediction of Aero-engine by Mingxing Huang, Lanying Yang, Gang Jiang, Xingan Hao, Hong Lu, Hang Luo, Peng Wang, Jinyang Li

“…Although deep learning models based on LSTM and Transformer have achieved significant results in this field, these models typically only extract temporal features, neglecting spatial features, and struggle with parallel computation, leading to a bottleneck in RUL prediction performance. …”
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Spatial‑temporal variability of water balance components in the North area of the Zailiisky Alatau Range by V. G. Konovalov, N. V. Pimankina

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A mixed modeling approach to predict the effect of environmental modification on species distributions. by Francesco Cozzoli, Menno Eelkema, Tjeerd J Bouma, Tom Ysebaert, Vincent Escaravage, Peter M J Herman

“…Human infrastructures can modify ecosystems, thereby affecting the occurrence and spatial distribution of organisms, as well as ecosystem functionality. …”
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Modelling Salmo trutta Complex Spatial Distribution in Central Italy: A Random Forest Approach Revealing Underrepresented Lowland Populations Based on Spatially‐Explicit Predictors... by Lorenzo Talarico, Elena Catucci, Marco Martinoli, Michele Scardi, Lorenzo Tancioni

“…The model shows (i) high predictive ability (K = 0.76), (ii) predicts suitable, naturally‐infrequent lowland watercourses where brown trout occurs or may occur. …”
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A High‐Performance Coupled Human And Natural Systems (CHANS) Model for Flood Risk Assessment and Reduction by Haoyang Qin, Qiuhua Liang, Huili Chen, Varuna DeSilva

“…In this study, we propose a novel Coupled Human And Natural Systems (CHANS) modeling framework to capture the intricate interactive human behaviors and flooding process at a high spatial resolution. …”
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Modeling the impact of climate change on corvus species distribution in Somaliland: Bayesian spatial point process approach for conservation by Abdisalam Hassan Muse, Maysaa Elmahi Abd Elwahab

“…IntroductionThis study aimed to predict the spatial distribution of Corvus edithae (Somali crow) in Somaliland and explore its relationship with climatic covariates.MethodsWe applied a log-Gaussian Cox process model, utilizing the R-INLA package. …”
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Urban environmental and population factors as determinants of COVID-19 severity: A spatially-resolved probabilistic modeling approach. by Jacob Roxon, Marie-Sophie Dumont, Eric Vilain, Mircea T Sofonea, Roland J-M Pellenq

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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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Spatial and social determinants of tuberculosis in the Brazilian Amazon: a five-year multilevel and cluster-based analysis in Pará state, 2018-2022 by C. Andrade-Sales, P. A. Mendonça-Cavalcante, A. P. Simões-Castro, M. P. Moreira-Sena, A. P. Galvão-Fonseca, A. G. N. Cardoso-Mello, C. A. Abreu-Alberio, J. L. Fernandes-Vieira, L. W. Pereira-Sena

“…The findings underscore the importance of integrating spatial epidemiology with multilevel modeling to uncover both individual and territorial determinants of tuberculosis. …”
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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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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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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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