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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Spectral Energy Density in an Axisymmetric Galaxy as Predicted by an Analytical Model for the Maxwell Field by Mayeul Arminjon

“…An analytical model for the Maxwell radiation field in an axisymmetric galaxy, proposed previously, is first checked for its predictions of the spatial variation of the spectral energy distributions (SEDs) in our Galaxy. …”
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Comprehensive propagation of errors for the prediction of woody biomass by Stephen H. Roxburgh, Keryn I. Paul

“…Recommendations for reducing errors in predicted biomass include increasing field survey sample size, adopting field survey designs that ensure spatial representativeness and improving moisture content measurement protocols and increasing the moisture content sample size during allometric model development. …”
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Electric Vehicle Charging Demand Prediction Model Based on Spatiotemporal Attention Mechanism by Yang Chen, Zeyang Tang, Yibo Cui, Wei Rao, Yiwen Li

“…The experimental results indicate that the proposed model has a more powerful comprehensive ability to capture spatiotemporal relationships and improve accuracy and stability in different prediction steps.…”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…Methods This study leverages a pre-trained model with spatial awareness to enhance the prediction of protein-ligand binding affinity. …”
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ST-GAT Resident OD Prediction Model Based on Mobile Signaling Data by Xianguang Jia, Weijie Fang, Yingying Lyu, Jinke Zhang, Mengyi Guo, Dong Li, Jie Qu, Fengxiang Guo

“…In this paper, this model is compared with the existing ST-GCN, DMS, GMM, PSAM-CNN, ST-Transformer, and COMD models, and the experimental results show that the predicted values of the ST-GAT model have a significant improvement in the prediction accuracy compared to other models. …”
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Prediction of quality software quality indicators with applied modifications of integrated gradiates methods by Anton Shantyr, Olha Zinchenko, Kamila Storchak, Andrii Bondarchuk, Yuriy Pepa

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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

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Regional Tropospheric Delay Prediction Model Based on LSTM-Enhanced Encoder Network by Yuanfang Peng, Chenglin Cai, Zexian Li, Kaihui Lv, Xue Zhang, Yihao Cai

“…In addition, we compared the spatial and temporal properties of the proposed model with those of the GPT3 and ERA5 models. …”
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A Microscopic Prediction Model for Traffic Noise in Adjacent Regions to Arterial Roads by Ming LI, Jizhou LIU

“…To determine this impact magnitude, this paper proposes and validates a microscopic level method that locally predicts the total noise level and the spectral characteristics of traffic flow in the near-road region. …”
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Drought Prediction Model of Pearl River Basin Based on SST and Machine Learning by FENG Xin, LIU Yanju, TONG Hongfu, QIAN Shuni

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Research on water quality prediction of Jiangshan Port based on SCV-CBA model by Yiting Xu, Zhaoju Liu

“…CNN was employed to capture spatial patterns in the data, while BiLSTM network modelled temporal dependencies. …”
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Predicting transient response using data-driven models for ball-impact simulations by Ross Pivovar, Fei Chen, Raghunath Katragadda, Vidyasagar Ananthan

“…This study investigates the application of machine learning (ML) models for predicting transient responses in ball-impact elastodynamics simulations. …”
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Research on Stock Index Prediction Based on the Spatiotemporal Attention BiLSTM Model by Shengdong Mu, Boyu Liu, Jijian Gu, Chaolung Lien, Nedjah Nadia

“…Stock index fluctuations are characterized by high noise and their accurate prediction is extremely challenging. To address this challenge, this study proposes a spatial–temporal–bidirectional long short-term memory (STBL) model, incorporating spatiotemporal attention mechanisms. …”
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Spatio-Temporal Graph Neural Networks for Streamflow Prediction in the Upper Colorado Basin by Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

“…This study presents a spatio-temporal graph neural network (STGNN) model for streamflow prediction in the Upper Colorado River Basin (UCRB), integrating graph convolutional networks (GCNs) to model spatial connectivity and long short-term memory (LSTM) networks to capture temporal dynamics. …”
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IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

“…Furthermore, Back Propagation Neural network model (BP), Spatial Autoregressive model (SAR) and MSVR model were adopted to perform the stress prediction, and the stress prediction accuracy from these models was analyzed. …”
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Automated Cardiac Disease Prediction Using Composite GAN and DeepLab Model by Sohail Jabbar, Umar Raza, Muhammad Asif Habib, Muhammad Farhan, Saqib Saeed

“…The Generator maps noise vectors to synthetic MRIs while the Discriminator predicts disease labels and classifies images as real/fake. …”
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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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