A Regional Investigation of Inverse Distance Weighting Particulate Matter Prediction within Kirkuk City, Iraq by Huda Jamal Jumaah, Wafaa Abbas Hasan, Sarah Jamal Jumaah

“…The results indicated a good fit for the prediction determined by the analysis. Moreover, the health risks have also been detected from the spatial distribution of each pollutant. …”
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A Prediction-Based Anomaly Detection Method for Traffic Flow Data with Multi-Domain Feature Extraction by Xianguang Jia, Jie Qu, Yingying Lyu, Mengyi Guo, Jinke Zhang, Fengxiang Guo

“…The prediction model is built as follows: first, Bidirectional Long Short-Term Memory network (Bi-LSTM) and a Graph Attention Network (GAT) extract temporal and spatial features, respectively. …”
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Prediction of Chemical Corrosion Rate and Remaining Life of Buried Oil and Gas Pipelines in Changqing Gas Field by Xianbing Li, Rui Liu, Dong Ma, Yang Bai, Yukai Shi, Badm Anhouck

“…Comparative analysis with other swarm intelligence algorithms shows that the improved particle swarm algorithm has stronger convergence ability and higher prediction accuracy than the BP model and SVM model. …”
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What Is My Plaza for? Implementing a Machine Learning Strategy for Public Events Prediction in the Urban Square by Jumana Hamdani, Pablo Antuña Molina, Lucía Leva Fuentes, Hesham Shawqy, Gabriella Rossi, David Andrés León

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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…These methods collectively optimize prediction accuracy and resource management. The result shows that the suggested model significant improvement in precision, recall, and F1-Score for crop yield, reaching 93 %, 94 %, and 93 %, implemented using Python software. …”
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Investigating the impacts of telecommuting on the spatial, temporal, and modal distribution of travel using an agent-based transport simulation model by Bijoy Saha, Mahmudur Rahman Fatmi, Nazmul Arefin Khan

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Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer by Taishi Nishizawa, Takouhie Maldjian, Zhicheng Jiao, Tim Q. Duong

“…The model integrates 3D convolutional neural networks and self-attention to capture spatial and cross-modal interactions. …”
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Highly Sensitive Photoacoustic Imaging: A New Strategy for Ultrahigh Spatial Resolution Seismic Physical Model Imaging by Xin Liu, Wen Wang, Qiangzhou Rong, Baozhi Yu

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Trackwise Prediction of GNSS-R Delay–Doppler Maps With DDM-PredRNN Network by Weichen Sun, Xiaochen Wang, Bing Han, Dongkai Yang

“…This article introduces an advanced deep learning framework DDM-PredRNN for predicting DDM in previously unobserved regions. Employing a spatiotemporal long short-term memory network with a PredRNN architecture, this model integrates axial attention to capture and leverage the delay/Doppler features embedded within the DDM, thereby enhancing the extraction of complex spatiotemporal characteristics. …”
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Statistical damage constitutive model of cemented sand and gravelbased on a modified spatially mobilized plane yield criterion by Jiangui Yang, Honglei Ren, Qiang Li, Shuling Cai

“…The physical significance of the WeibullWeibull distribution parameters m and F0 was examined, and the variation of these parameters with respect to gel content and confining pressure was analyzed and modified. Finally, the predicted results of the proposed model were compared with experimental values and those from other constitutive models. …”
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Intelligent prediction method for fire temperature fields in underground exhibition spaces of high-intensity urban areas by Yuan Shi, Yang Zhou, Guanhua Qu, Lan Wang, Rong Wang, Zenghui Liu

“…This study aims to elucidate the influence mechanisms of spatial characteristics on fire temperature fields and innovatively proposes a temperature field prediction method based on distributed fiber optic temperature sensors. …”
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Formation Mechanism and Prediction Method for the Permian Fused Breccia Tuff Reservoir, Wuxia Region, Junggar Basin by Duonian Xu, Jianguo Pan, Shuxin Pan, Bin Gao, Lu Yin, Yongqiang Qu, Lei Zhang

“…The 3D seismic amplitude attributes were then extracted to predict the extent of the reservoir, yielding prediction results consistent with the drilling observations.…”
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Enhanced prediction of heat transfer in jet impingement cooling using an artificial intelligence: A case study by Mehmet Berkant Özel, Ufuk Durmaz, Muhammed Ali Nur Öz, Ahmet Ümit Tepe, Cemil Öz, Ünal Uysal, Orhan Yalçinkaya, Ali Cemal Beni̇m, Norah Alomayrah, M.S. Al-Buriahi

“…The goal is to understand how accurate and fast deep learning models with limited data can deliver predictions for complex systems such as jet impingement cooling. …”
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GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts by Haochen Chen, Tao Liang, Kai Tan, Anan Wu, Xin Lu

“…This trend is consistent across other graph-based NMR chemical shift prediction methods as well. Therefore, while employing GT-NMR or other graph-based methods for the rapid and routine prediction of NMR chemical shifts, it is advisable to utilize nSPS to assess their suitability. …”
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Baseline MRI habitat imaging for predicting treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer by Muzhen He, Huijian Chen, Chao Xu, Zhibo Wu, Zijie Lin, Yang Song, Guang Yang, Mingping Ma, Fangqin Xue

“…Decision curve analysis demonstrated that the clinical combined habitat model (ModelClinic+Habitat) provided higher net benefits than other models within a threshold probability range of 20% to 80%.ConclusionThe habitat model we developed, which integrates first-order and clinical features, demonstrates potential for predicting the efficacy of nCRT clinically interpretable spatial heterogeneity information. …”
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Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai, Qilin He

“…The models achieved high predictive accuracy, with NSE values of 0.918, 0.946, 0.936, 0.967, and 0.887 for NO₃⁻-N, NH₄⁺-N, TN, EC, and Cl⁻, respectively, demonstrating their robustness. …”
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An improved graph neural network integrating indicator attention and spatio-temporal correlation for dissolved oxygen prediction by Fei Ding, Shilong Hao, Mingcen Jiang, Hongfei Liu, Jingjie Wang, Bing Hao, Haobin Yuan, Hanjie Mao, Yang Hu, Wenpan Li, Xin Xie, Yong Zhang

“…The BO-AM-MTGNN model proposed in this study effectively improves DO prediction accuracy. …”
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Degradation prediction of PEM water electrolyzer under constant and start-stop loads based on CNN-LSTM by Boshi Xu, Wenbiao Ma, Wenyan Wu, Yang Wang, Yang Yang, Jun Li, Xun Zhu, Qiang Liao

“…However, it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales. …”
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Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India by Imran Khan, Sarwar Nizam, Apoorva Bamal, Abdul Majed Sajib, Mir Talas Mahammad Diganta, Mohd Azfar Shaida, S.M. Ashekuzzaman, Stephen Nash, Agnieszka I. Olbert, Md Galal Uddin

“…This study employs the eXtreme Gradient Boosting (XGB) algorithm, demonstrating strong predictive capabilities within the RMS-WQI model across diverse aquifers of Rajasthan. …”
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Quantifying Root Cohesion Spatial Heterogeneity Using Remote Sensing for Improved Landslide Susceptibility Modeling: A Case Study of Caijiachuan Landslides by Zelang Miao, Yaopeng Xiong, Zhiwei Cheng, Bin Wu, Wei Wang, Zuwu Peng

“…This approach, integrated with land use-specific hydrological parameters and an infinite slope stability model, significantly improves landslide susceptibility predictions compared to models ignoring root cohesion or using uniform assignments. …”
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