Assessing spatial soil erosion under climate change using SWAT model in a semi-arid watershed of northeastern Tunisia by Fathia Jarray, Taoufik Hermassi, Haykel Sellami, Mohamed Ali Ben Abdallah, Mohamed Mechergui

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Advanced AI techniques for landslide susceptibility mapping and spatial prediction: A case study in Medellín, Colombia by I.N. Gómez-Miranda, C. Restrepo-Estrada, A. Builes-Jaramillo, João Porto de Albuquerque

“…This study presents a novel landslide susceptibility model that incorporates spatial and temporal dependencies, including landslide recurrence. …”
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Temperature-Dependent Modeling and Spatial Predictions for Identifying Geographical Areas in Brazil Suitable for the Use of <i>Cordyceps javanica</i> in Whitefly Control by Heloiza A. Boaventura, Lidiane A. Queirós, José Francisco A. Silva, Tarryn A. Goble, Kelly Pazolini, Allan F. Marciano, Eliane D. Quintela

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Vehicle Trajectory Prediction Algorithm Based on Hybrid Prediction Model with Multiple Influencing Factors by Tao Wang, Yiming Fu, Xing Cheng, Lin Li, Zhenxue He, Yuchi Xiao

“…In light of this limitation, we propose a vehicle trajectory prediction algorithm predicated on a hybrid prediction model. …”
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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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Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India by Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy

“…With machine learning models being the most utilized modeling technique for digital soil mapping (DSM), the implementation of model-based deep learning methods for spatial soil predictions is still under scrutiny. …”
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A High-Granularity, Machine Learning Informed Spatial Predictive Model for Epidemic Monitoring: The Case of COVID-19 in Lombardy Region, Italy by Lorenzo Gianquintieri, Andrea Pagliosa, Rodolfo Bonora, Enrico Gianluca Caiani

“…This study aimed at proposing a predictive model for real-time monitoring of epidemic dynamics at the municipal scale in Lombardy region, in northern Italy, leveraging Emergency Medical Services (EMS) dispatch data and Geographic Information Systems (GIS) methodologies. …”
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Deep Learning-Based Spatial Prediction of Landslide Risk in Coastal Areas Using GIS and Multicriteria Decision Making: A DeepLabV3+ Approach by Huyong Yan, Asad Khan, Ahsan Jamil, Belkendil Abdeldjalil, Taoufik Saidani, Nazih Y. Rebouh

“…The complex, nonlinear interconnections of environmental and human elements cause terrain instability and challenge conventional prediction methods. In this work, we offer a DeepLabV3+-based deep learning framework coupled with geographic information systems and multicriteria decision making methods for spatial prediction of landslide risk, over the Dubai coastal and urban region (covering approximately 4000 km²). …”
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FEN-MRMGCN: A Frontend-Enhanced Network Based on Multi-Relational Modeling GCN for Bus Arrival Time Prediction by Ting Qiu, Chan-Tong Lam, Bowie Liu, Benjamin K. Ng, Xiaochen Yuan, Sio Kei Im

“…The proposed module captures spatial relationships in dense, multi-route areas by using graph convolution layers based on multi-relational modeling to aggregate spatial information. …”
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The Impact Prediction of Income Tax Standards on Company Performance: A Hybrid Spatial Artificial Intelligence Approach by Sawsan Kareem Abdullah

“…In this study, various artificial intelligence methods such as artificial neural networks, support vector machines, deep learning, decision trees, random forests, and genetic algorithms were used in combination with spatial modeling. The results show that income tax accounting standards have a significant impact on the financial performance of companies, and the combination of artificial intelligence methods with spatial modeling significantly increases the prediction accuracy. …”
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Predicting of Temporal-Spatial Sand Dunes Transition Caused by Marine Storms (Case Study: The Coast of Makran, Iran) by Soleiman PirouzZadeh, Mahmood Khosravi, Samad Fotohi

“…The aim of this paper is  modeling and prediction of changes in  land-use in 2035 by using  CA Markov model and Landsat satellite images in the West of Zarabad,( The coasts of Makran). …”
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Predicting changes in land use and land cover using remote sensing and land change modeler by Brijmohan Bairwa, Rashmi Sharma, Arnab Kundu, Saad Sh. Sammen, Fahad Alshehri, Chaitanya Baliram Pande, Chaitanya Baliram Pande, Zoltan Orban, Ali Salem, Ali Salem

“…The integration of geo-spatial and remote sensing technologies is pivotal in comprehending these dynamics and formulating strategies for future natural resource management. …”
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Modeling to predict cases of hantavirus pulmonary syndrome in Chile. by Elaine O Nsoesie, Sumiko R Mekaru, Naren Ramakrishnan, Madhav V Marathe, John S Brownstein

“…We adopted an information-theoretic approach to model ranking and selection. Data from 2001-2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions.…”
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Impact of symmetry in local learning rules on predictive neural representations and generalization in spatial navigation. by Janis Keck, Caswell Barry, Christian F Doeller, Jürgen Jost

“…In spatial cognition, the Successor Representation (SR) from reinforcement learning provides a compelling candidate of how predictive representations are used to encode space. …”
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Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV by Lunyang Lin, Yuxiang Chen, Hong Xiong, Chunliang Yu, Hong Zhu, Yiyang Xing, Guodong Zheng

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DBSCAN-PCA-INFORMER-Based Droplet Motion Time Prediction Model for Digital Microfluidic Systems by Zhijie Luo, Bin Zhao, Wenjin Liu, Jianhua Zheng, Wenwen Chen

“…As chip usage frequency rises, device degradation introduces seasonal and trend patterns in droplet motion time data, complicating predictive modeling. This paper first employs the density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm to analyze the droplet motion time data in digital microfluidic systems. …”
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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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A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Moreover, in terms of ocean sound speed, most of these models predict an ocean sound speed profile (SSP) at a single coordinate position, and only a few predict multi-spatial-scale SSPs. …”
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Intermodel and method comparison of mean radiant temperature from numerical weather prediction models: Evaluation of enhanced spatial resolution in Europe by Oleh SKRYNYK, Pavol NEJEDLÍK, Krzysztof BŁAŻEJCZYK

“…Mean Radiant Temperature (MRT), derivable from numerical weather prediction (NWP) models, is a critical input for many such indices. …”
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Analysis and Prediction of Spatial and Temporal Land Use Changes in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains by Xiaoxu He, Zhaojin Yan, Yicong Shi, Zhe Wei, Zhijie Liu, Rong He

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