The impact of digital economy on energy conservation and emission reduction: Evidence from prefecture-level cities in China by Cheng Zhang, Yirui Zhang, Hua Zhang, Jiaying You, Xinke Lv, Xinyu Cheng

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Nonlinear prediction model of vehicle network traffic management based on the internet of things by Zhijie Peng, Lili Yin

“…This research presents a novel nonlinear prediction model for Internet of Things (IoT) driven vehicle network traffic management. …”
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Application of Multi-Scale Geological Modeling Technology in Sweet Spot Prediction of Shale Oil Reservoirs by HU Laidong, HUO Hanyong, GUAN Qianqian, TANG Caixia, TAO Ji, ZHANG Yuxuan

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Burn Severity in Canada's Mountain National Parks: Patterns, Drivers, and Predictions by Weiwei Wang, Xianli Wang, Wanli Wu, Futao Guo, Jane Park, Guangyu Wang

“…The predicted burn severity potentials of the whole parks in 2002 and 2012 showed overall consistent spatial patterns, and lightning‐caused fires produced more high‐severity burn areas than prescribed fires. …”
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Development of a Predictive Model for N-Dealkylation of Amine Contaminants Based on Machine Learning Methods by Shiyang Cheng, Qihang Zhang, Hao Min, Wenhui Jiang, Jueting Liu, Chunsheng Liu, Zehua Wang

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When Time Prevails: The Perils of Overlooking Temporal Landscape Evolution in Landslide Susceptibility Predictions by Jinping Liu, Panxing He, Jianhua Xiao, Qingfeng Hu, Yanqun Ren, Aiding Kornejady, Huiran Gao

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A Digital Shadow for Modeling, Studying and Preventing Urban Crime by Juan Palma-Borda, Eduardo Guzman, Maria-Victoria Belmonte

“…The performance indicators of the model after being calibrated, in terms of the metrics widely used in predictive policing, suggest that our simulated crime generation matches the general pattern of crime in the city according to historical data. …”
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Wide-Area Active Frequency Control with Multi-Step-Size MPC by Yan Xie, Shiying Ma, Jiakai Shen, Xiaojun Tang, Jianmiao Ren, Liwen Zheng

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A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin by Hugo J. M. Miniere, Ernesto A. B. F. Lima, Guillermo Lorenzo, David A. Hormuth II, Sophia Ty, Amy Brock, Thomas E. Yankeelov

“…To better personalize therapies, it is essential to develop tools capable of identifying and predicting intra- and inter-tumor heterogeneities. Biology-inspired mathematical models are capable of attacking this problem, but tumor heterogeneity is often overlooked in in-vivo modeling studies, while phenotypic considerations capturing spatial dynamics are not typically included in in-vitro modeling studies. …”
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Performance Evaluation of Real-Time Image-Based Heat Release Rate Prediction Model Using Deep Learning and Image Processing Methods by Joohyung Roh, Sehong Min, Minsuk Kong

“…For comparative analysis, the YOLO segmentation model was used. Furthermore, the fire diameter and flame height were determined from the spatial information of the segmented flame, and the HRR was predicted based on the correlation between flame size and HRR. …”
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NDVI Prediction with RGB UAV Imagery Utilizing Advanced Machine Learning Regression Models by I. Aydin, U. G. Sefercik

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Optimizing Clinical Management of COVID-19: A Predictive Model for Unvaccinated Patients Admitted to ICU by Ahmed Farhan, Khouloud Ayed, Sara Zayati, Rym Akrout, Akram Dlala, Amal Abouda, Nesrine Zoghlami, Halima Mahjoubi, Iheb Labbane, Asma Gati

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ReScConv-xLSTM: An improved xLSTM model with spatiotemporal feature extraction capability for remaining useful life prediction of Aero-engine by Mingxing Huang, Lanying Yang, Gang Jiang, Xingan Hao, Hong Lu, Hang Luo, Peng Wang, Jinyang Li

“…Although deep learning models based on LSTM and Transformer have achieved significant results in this field, these models typically only extract temporal features, neglecting spatial features, and struggle with parallel computation, leading to a bottleneck in RUL prediction performance. …”
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Identifying key aspects to enhance predictive modeling for early identification of schistosomiasis hotspots to guide mass drug administration. by Yewen Chen, Fangzhi Luo, Leonardo Martinez, Susan Jiang, Ye Shen

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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

“…The findings indicate that Random Forest, Support Vector Machine (SVM), and Artificial Neural Network (ANN) are the most frequently used algorithms, with prediction accuracy ranging from 72% to 99.92%. Dominant predictor variables include maternal education, economic status, sanitation, and spatial-temporal data. …”
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Research on spatial prediction technology for mitigating tunnel inrush disasters under complex geological conditions in China’s Hengduan Mountain Range by Yang Zou, XiuJun Dong, Tao Feng, ZhengXuan Xu, Hailin He, ZhangLei Wu

“…This spatial prediction and analysis method is highly effective and has practical and promotional value.…”
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Identifying species traits that predict vulnerability to climate change by Damien A. Fordham

“…A powerful solution is to analyse the growing volume of biological data on changes in species ranges and abundances using process-explicit ecological models that run at fine temporal and spatial scales and across large geographical extents. …”
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A Novel Model for Predicting PM2.5 Concentrations Utilizing Graph Convolutional Networks and Transformer by Yuan Huang, Feilong Han, Qimeng Feng

“…To enhance the model’s predictive performance, we designed a new Transformer architecture named FFPformer, which incorporates the Fast Fourier Transform into the Transformer framework. …”
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Topographic Position Index Predicts Within-Field Yield Variation in a Dryland Cereal Production System by Jacob A. Macdonald, David M. Barnard, Kyle R. Mankin, Grace L. Miner, Robert H. Erskine, David J. Poss, Sushant Mehan, Adam L. Mahood, Maysoon M. Mikha

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Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning by Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist

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