Deep spatio-temporal dependent convolutional LSTM network for traffic flow prediction by Jie Tang, Rong Zhu, Fengyun Wu, Xuansen He, Jing Huang, Xianlai Zhou, Yishuai Sun

“…Secondly, for time features, most scholars use time series prediction models, such as recurrent neural networks and their variants. …”
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Checkpoint data-driven GCN-GRU vehicle trajectory and traffic flow prediction by Deyong Guan, Na Ren, Ke Wang, Qi Wang, Hualong Zhang

“…The results show that compared with the single models GCN, GRU, BiGRU, and BiLSTM, the GCN-GRU model has reduced the MAE by 0.75, 0.46, 0.52, and 0.57, and the RMSE by 0.76, 0.52, 0.58, and 0.68, respectively, demonstrating stronger spatial and temporal correlation characteristics and higher prediction accuracy. …”
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Surrogate model for calculating spatial magnetic track forces in permanent magnet levitation transportation by LIU Haodong, FENG Yang, ZHAO Chunfa, LUO Shihui, SONG Xiaolin

“…Developing a method for rapidly and accurately calculating magnetic forces, which considers multi-degree-of-freedom spatial attitudes, is essential for the dynamic prediction and assessment of PML vehicles. …”
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Evaluation of machine learning and deep learning algorithms for fire prediction in Southeast Asia by Aditya Eaturu, Krishna Prasad Vadrevu

“…By tailoring models to specific regional fire data, prediction accuracy and responsiveness can be enhanced, ultimately improving fire risk management in Southeast Asia and beyond.…”
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The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains by Sujing Ding, Qiang Sun, Yan Guo, Xiao Wei

“…Subsequently, the ConvGRU spatiotemporal prediction model was employed to investigate the prospective trajectory of vegetation NPP in the HRB. …”
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Digital mapping of Ghana’s soil properties and nutrients: performance of spline and weighted average approaches by Kora B.D. Simperegui, Anselme K.K. Kouame, Benjamin Kwesie, Prem S. Bindraban, William Adzawla, Eric Asamoah, Mohamed El Gharous

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Spatial age-stratified epidemiological model with applications to South African COVID-19 pandemic by Raeesa Manjoo-Docrat, Nada Abdelatif, Jenny Holloway, Nontembeko Dudeni-Tlhone, Claudia Dresselhaus, Elona Mbayise, Charl Janse van Rensburg, Inger Fabris-Rotelli, Pravesh Debba, Sibusisiwe Makhanya

“…Results: The spatial age-stratified model produced more biologically plausible and accurate predictions compared to non-stratified models investigated. …”
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Temporal and Spatial Variation in Habitat Quality in Guangxi Based on PLUS-InVEST Model by Chuntian Pan, Jun Wen, Jianing Ma

“…This study systematically analyzes the spatial and temporal dynamics of land use and habitat quality in Guangxi from 2000 to 2020 using the PLUS-InVEST model and simulates future scenarios for 2030. …”
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LSTGINet: Local Attention Spatio-Temporal Graph Inference Network for Age Prediction by Yi Lei, Xin Wen, Yanrong Hao, Ruochen Cao, Chengxin Gao, Peng Wang, Yuanyuan Guo, Rui Cao

“…First, multi-scale temporal and spatial branches are used to increase the receptive field and model the age information simultaneously, achieving the perception of static correlation. …”
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Multimodal Learning for Traffic Risk Prediction: Combining Aerial Imagery With Contextual Data by Hanlin Tian, Yuxiang Feng, Mohammed Quddus, Yiannis Demiris, Panagiotis Angeloudis

“…Using DeepLabV3+, UNet++, and SegFormer as baseline models, we demonstrate that combining building and traffic data enhances prediction accuracy compared to models relying solely on visual data. …”
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Dynamic–statistic combined ensemble prediction and impact factors of China's summer precipitation by X. Wang, Z. Yang, S. Li, Q. Li, G. Feng, G. Feng

“…<p>​​​​​​​The dynamic–statistic prediction shows excellent performance with regard to monthly and seasonal precipitation prediction in China and has been applied to several dynamical models. …”
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Ecological risk assessment and response prediction caused by LUCC in the central Yunnan Province by Yongdong Zhang, Zisheng Yang, Renyi Yang, Fuhua Liu, Yimei He, Linlin Cao, Jinrong Yang, Jiayi Zhang

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Forest Loss and Susceptible Area Prediction at Sefwi Wiawso District (SWD), Ghana by William Osei-Wusu, Jonathan Quaye-Ballard, Terah Antwi, Naa Lamkai Quaye-Ballard, Alfred Awotwi

“…The impacts of selected spatial variables on forest losses were examined using retrospective and predictive approaches. …”
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Enhancing bathymetric prediction by integrating gravity and gravity gradient data with deep learning by Junhui Li, Nengfang Chao, Nengfang Chao, Houpu Li, Gang Chen, Gang Chen, Shaofeng Bian, Zhengtao Wang, Aoyu Ma

“…This study aims to enhance the spatial resolution and accuracy of bathymetric prediction by integrating Gravity Anomaly (GA) and Vertical Gravity Gradient Anomaly (VGG) data with a dual-channel Backpropagation Neural Network (BPNN). …”
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Prediction on rock strength by mineral composition from machine learning of ECS logs by Dongwen Li, Xinlong Li, Li Liu, Wenhao He, Yongxin Li, Shuowen Li, Huaizhong Shi, Gaojian Fan

“…Although the Transformer model was less computationally efficient, it exhibited strengths in predicting subsurface strength parameters, particularly in capturing spatial variations and forecasting these parameters across different spatial locations. …”
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Spatially Explicit Model for Assessing the Impacts of Groundwater Protection Measures in the Vicinity of the Hranice Abyss by Jozef Sedláček, Hana Vavrouchová, Kryštof Chytrý, Ondřej Ulrich, Petra Oppeltová, Milan Geršl, Kristýna Kohoutková, Radim Klepárník, Petr Kučera, Vítězslav Vlček, Jana Šimečková, Eva Žallmannová

“…The model employs a multi-criteria decision analysis, integrated with hydrological modeling and a high-resolution random forest-based prediction algorithm, to downscale land surface temperature (LST) in order to obtain high-resolution 1 × 1 m spatial results. …”
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Application Research of Cross-Attention Mechanism for Traffic Prediction Based on Heterogeneous Data by Feng Zhihao

“…This cutting-edge model efficiently integrates and analyzes complex spatial-temporal data. …”
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Improving the accuracy of rainfall prediction using a regionalization approach and neural networks by Mohammad Arab Amiri, Christian Conoscenti, Mohammad Saadi Mesgari

“… Spatial and temporal analysis of precipitation patterns has become an intense research topic in contemporary climatology. …”
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Gridded global dataset of industrial water use predicted using the Random Forest by Manas Ranjan Panda, Yeonjoo Kim

“…We propose a random forest regression model to predict IWU at a spatial resolution of 0.5° by combining socioeconomic, climatic, and geographical datasets. …”
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A comprehensive survey of the machine learning pipeline for wildfire risk prediction and assessment by Naveed Ejaz, Salimur Choudhury

“…This survey offers a comprehensive overview of machine learning approaches for wildfire risk prediction and assessment, encompassing the entire pipeline from data acquisition to model deployment. …”
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