Spatial Prediction of Soil Water Content by Bayesian Optimization–Deep Forest Model with Landscape Index and Soil Texture Data by Weihao Yang, Ruofan Zhen, Fanyue Meng, Xiaohang Yang, Miao Lu, Yingqiang Song

“…A Bayesian optimization–deep forest (BO–DF) model was developed to leverage these indices for predicting the spatial variability of SWC. …”
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Separable Reversible Data Hiding in Encrypted 3D Mesh Models Based on Spatial Clustering and Multi-MSB Prediction by Y. Mao, Y. Xu

“…Input model vertices are partitioned into exclusive clusters through spatial clustering, ensuring close proximity within each cluster. …”
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Coupled intelligent prediction model for medium- to long-term runoff based on teleconnection factors selection and spatial-temporal analysis. by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

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Promoting global sustainable development: spatial spillover effects of higher education on economic and ecological sustainability by Daozheng Li, Xiaoxiao Sun, Tongning Li

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Numerical Modeling of PMSM Noise Reduction by Harmonic Current Injection by Federico Soresini, Dario Barri, Federico Ballo, Massimiliano Gobbi

“…This order turns out to be dominated by a spatial 0 mode also referred to as the breathing mode. …”
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A homotopy estimation based temporal-spatial spectrum prediction for UAV communications with arbitrary flight paths by Shan Luo, Wenjun Zhou, Lifan Wu, Qixiang Zhang, Rongping Lin, Yao Yan, Hui Li, Siyu Xie

“…This paper introduces a temporal-spatial spectrum prediction approach for arbitrary flight within a specific region. …”
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InSAR-RiskLSTM: Enhancing Railway Deformation Risk Prediction with Image-Based Spatial Attention and Temporal LSTM Models by Baihang Lyu, Ziwen Zhang, Heinz D. Fill

“…To address these limitations, this study introduces InSAR-RiskLSTM, a novel framework that leverages the high-resolution and wide-coverage capabilities of Interferometric Synthetic Aperture Radar (InSAR) to enhance railway deformation risk prediction. The primary objective of this study is to develop an advanced predictive model that accurately captures both temporal dependencies and spatial susceptibilities in railway deformation processes. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

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An epidemical model with nonlocal spatial infections by Su Yang, Weiqi Chu, Panayotis Kevrekidis

“…Generalizing this ordinary differential equation (ODE) framework into a spatially distributed partial differential equation (PDE) model is a considerable challenge. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

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The nexus between poverty reduction and carbon emissions: Insights from Hubei, China during the Targeted Poverty Alleviation Period by Mengxiao Liu, Yong Ge

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Modeling and mapping spatial distribution of baseline soil organic carbon stock, a case of West Hararghe, Oromia Regional State, Eastern Ethiopia by Martha Kidemu Negassa, Mitiku Haile, Gudina Legesse Feyisa, Lemma Wogi, Feyera Merga

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The Spatial Network Characteristics of the Coupling Coordination Degree Between Pollution and Carbon Reduction and High-Quality Development in the Yangtze River Economic Belt by Mengjiao Fan, Ying Wang, Sheng Ye, Chao Wei, Zhibin Xue

“…The coupling and coordination degree between pollution, carbon reduction, and high-quality development of 110 cities in the Yangtze River Economic Belt from 2010 to 2021 was measured, and the modified gravity model and social network analysis were then employed to assess the spatial network characteristics, patterns, and structure evolution. …”
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Prediction of land use around urban metro stations using the CA-Markov model by Xingzhong Nong, Ming Geng, Xia Jia

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Prediction Modeling and Driving Factor Analysis of Spatial Distribution of CO₂ Emissions from Urban Land in the Yangtze River Economic Belt, China by Chao Wang, Jianing Wang, Le Ma, Mingming Jia, Jiaying Chen, Zhenfeng Shao, Nengcheng Chen

“…Based on socioeconomic grid data, such as nighttime lights and the population, this study proposes a spatial prediction method for CO₂ emissions from urban land using a Long Short-Term Memory (LSTM) model with added fully connected layers. …”
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Multi-Task Learning-Based Traffic Flow Prediction Through Highway Toll Stations During Holidays by Xiaowei Liu, Yunfan Zhang, Zhongyi Han, Hao Qiu, Shuxin Zhang, Jinlei Zhang

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Combination of spatial and temporal de-noising and artifact reduction techniques in multi-channel dry EEG by Milana Komosar, Gabriella Tamburro, Gabriella Tamburro, Uwe Graichen, Silvia Comani, Silvia Comani, Jens Haueisen

“…IntroductionDry electroencephalography (EEG) allows for recording cortical activity in ecological scenarios with a high channel count, but it is often more prone to artifacts as compared to gel-based EEG. Spatial harmonic analysis (SPHARA) and ICA-based methods (Fingerprint and ARCI) have been separately used in previous studies for dry EEG de-noising and physiological artifact reduction. …”
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Can transparency governance promote interregional coordinated carbon emission reduction? A new perspective from China provincial transparency index by Nan Jiang, Juan Huang

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I.S.G.E.: An Integrated Spatial Geotechnical and Geophysical Evaluation Methodology for Subsurface Investigations by Christos Orfanos, Konstantinos Leontarakis, George Apostolopoulos, Ioannis E. Zevgolis, Bojan Brodic

“…The automatically derived 3D models, depicting the spatial distribution of specific geotechnical parameters, provide engineers with an additional interpretation tool for better understanding the subsurface conditions of a survey area.…”
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Spatial and temporal model for WQI prediction based on back-propagation neural network, application on EL MERK region (Algerian southeast) by Saber Kouadri, Samir Kateb, Rachid Zegait

“…The test shows that the model is suitable for predicting WQI with an error rate of 9.3%.…”
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