Spatial modeling of two mosquito vectors of West Nile virus using integrated nested Laplace approximations by Kristin J. Bondo, Diego Montecino‐Latorre, Lisa Williams, Matt Helwig, Kenneth Duren, Michael L. Hutchinson, W. David Walter

“…We observed different spatial patterns of abundance in the predictive risk maps of each of the species. …”
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Modeling and Prediction of Mixed Errors in Feed Systems Based on Digital Twins by HUANG Hua, MEI Le, ZHI Xiaobo, ZHANG Huiwang

“…Finally, the proposed method is validated using spiral spatial trajectories. Experimental results demonstrate that the error twin model improves prediction accuracy by 76. 04% compared to traditional mechanism models and achieves superior accuracy compared to similar neural network models. …”
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Modeling, Assessment, and Prediction of Carbon Storage in Hebei–Tianjin Coastal Wetlands by Liang Zhao, Hui Gao, Jintong Liu, Feng Wang, Tonggang Fu

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Spatial risk patches of the Indian crested porcupine crop damage in southeastern Iran by Kamran Almasieh, Alireza Mohammadi

“…Conservation areas covered about 8% of the predicted spatial risk patches and 2.4% of the hotspots of agricultural damage, respectively. …”
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Network level spatial temporal traffic forecasting with Hierarchical-Attention-LSTM by Tianya Zhang

“…This paper leverages diverse traffic state datasets from the Caltrans Performance Measurement System (PeMS) hosted on the open benchmark and achieved promising performance compared to well-recognized spatial-temporal prediction models. Drawing inspiration from the success of hierarchical architectures in various Artificial Intelligence (AI) tasks, cell and hidden states were integrated from low-level to high-level Long Short-Term Memory (LSTM) networks with the attention pooling mechanism, similar to human perception systems. …”
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Characterizing US Spatial Connectivity and Implications for Geographical Disease Dynamics and Metapopulation Modeling: Longitudinal Observational Study by Giulia Pullano, Lucila Gisele Alvarez-Zuzek, Vittoria Colizza, Shweta Bansal

“…ObjectiveThis study aimed to address the questions that are critical for developing accurate transmission models, predicting the spatial propagation of disease across scales, and understanding the optimal geographical and temporal scale for the implementation of control policies. …”
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Preliminary Mapping of the Spatial Variability in the Microclimate in Tropical Greenhouses: A Pepper Crop Perspective by Angel Triana, Alfonso Llanderal, Pedro García-Caparrós, Manuel Donoso, Rafael Jiménez-Lao, John Eloy Franco Rodríguez, María Teresa Lao

“…The objectives of this experiment were to (1) discern the spatial variability in climatic parameters within a greenhouse throughout different phenological stages of pepper cultivation and (2) develop an empirical model aimed at establishing predictive equations for temperature, relative humidity, vapor pressure deficit, and crop evapotranspiration (ETc) within the greenhouse considering the climatic parameters recorded on the outside. …”
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OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION by Mohammed Shukur Alfaras, Oğuz Karan, Sefer Kurnaz

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Development and Spatial External Validation of a Predictive Model of Survival Based on Random Survival Forest Analysis for People Living With HIV and AIDS After Highly Active Antiretroviral Therapy in China: Retrospective Cohort Study by Xiaoshan Li, Yanhui Li, Zhengping Zhu, Bingxin Tan, Xiaoyi Zhou, Hongjie Shi, Xin Li, Ping Zhu, Yuanyuan Xu

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Random Cross-Validation Produces Biased Assessment of Machine Learning Performance in Regional Landslide Susceptibility Prediction by Chandan Kumar, Gabriel Walton, Paul Santi, Carlos Luza

“…Machine learning (ML) models are extensively used in spatial predictive modeling, including landslide susceptibility prediction. …”
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GIS-based multi-criteria predictive modelling for geothermal energy exploration by Andongma Wanduku Tende, Mamidak Miner Iiiya, Serah Habu, Jiriko Nzeghi Gajere, Shekwonyadu Iyakwari, Mohammed Dahiru Aminu

“…The weighted sum model was then used to develop geothermal predictive maps while the accuracy of prediction was determined using the receiver operating characteristic/area under curve (ROC/AUC) analysis. …”
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Temporal–Spatial Partial Differential Equation Modeling of Land Cover Dynamics via Satellite Image Time Series and Sparse Regression by Ming Kang, Zheng Zhang, Zhitao Zhao, Keli Shi, Junfang Zhao, Ping Tang

“…Land cover dynamics play a critical role in understanding environmental changes, but accurately modeling these dynamics remains a challenge due to the complex interactions between temporal and spatial factors. …”
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Spatial Analysis of Rural Architecture Structure in Passive Defense by VIKOR Modeling; Case study: Yaseh Chai Village by Kourosh Momeni, Mostafa Mohebian, Elias Mavedat

“…Based on the results obtained from the VIKOR modeling, the spatial analysis of the architectural and urban structure of Yaseh Chai village is based on non-operational defense criteria, such as "hiding the village's appearance with local materials" and "predicting the stair-shaped form of houses to reduce damage caused by the destruction of houses" as well as "suitable village location based on suitable and fertile soil for agriculture, horticulture and farming to provide for the economic needs of the inhabitants." …”
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From maps to models: Key concepts in Geographic Information Systems by Yohannes Shifera Daka, Kassaye Hussein, Ashenafi Yimam

“…These models help predict and analyze spatial dynamics across time by simulating real-world phenomena. …”
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SCS-Net: Stratified Compressive Sensing Network for Large-Scale Crowd Flow Prediction by Xiaoyong Tan, Kaiqi Chen, Min Deng, Baoju Liu, Zhiyuan Zhao, Youjun Tu, Sheng Wu

“…However, achieving accurate and efficient prediction remains challenging. Most existing models overlook spatial heterogeneity, employing unified parameters to fit diverse crowd flow patterns across different spatial units, which limits their accuracy. …”
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Genetic Programming-Based Prediction Model for Microseismic Data by Man Wang, Hongwei Zhou, Dongming Zhang, Yingwei Wang, Weihang Du, Beichen Yu

“…Therefore, we collected a large amount of microseismic data obtained from the working faces of Shoushan Mine of Pingdingshan Coal Group in China and filtered the data, then we constructed a prediction model of microseismic data based on underground spatial three-dimensional coordinates using genetic programming (GP), which can realize real-time monitoring and disaster warning of microseismic signals. …”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…Additionally, the sparrow search algorithm (SSA) is employed to optimize hyperparameters, further improving the model’s performance. Unlike traditional approaches that rely on time-axis-based analysis, this study uses the working face advancement distance as the basis for prediction, which better reveals the potential spatial correlations of rockburst occurrences, aligning with engineering practice needs.Validation using microseismic monitoring data from a coal mine demonstrates that the proposed model achieves a prediction accuracy of 93.62% and an F1-score of 93.54%. …”
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Increasing neural network robustness improves match to macaque V1 eigenspectrum, spatial frequency preference and predictivity. by Nathan C L Kong, Eshed Margalit, Justin L Gardner, Anthony M Norcia

“…They also suggest that it may be useful to penalize slow-decaying eigenspectra or to bias models to extract features of lower spatial frequencies during task-optimization in order to improve robustness and V1 neural response predictivity.…”
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Spatial-Temporal Distribution Prediction of Electric Vehicle Charging Load Considering Charging Behavior and Real-Time SOC by ZHANG Linjuan, LI Wenfeng, XU Changqing, GUO Jianyu, ZHANG Xiawei, YUAN Jia, WANG Yaoqiang

“…[Methods] The influence of traffic conditions and ambient temperature on EV energy consumption and charging behavior is analyzed，and road traffic network and comprehensive energy consumption models are established. Based on the user's travel chain，the user's travel characteristics are analyzed，the shortest time method is used to plan the driving path，and a spatial-temporal distribution prediction model of the EV charging load is built considering the charging queue time and real-time SOC. …”
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Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. by Xixian Zheng, Wenmei Liao

“…Additionally, a Combination Forecasting Model predicts CCD trends through 2030. The findings indicate positive trends in both ACEE and FS, albeit with significant regional disparities and a notable lag of FS behind ACEE improvement. …”
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