Ensembles of Gradient Boosting Recurrent Neural Network for Time Series Data Prediction by Shiqing Sang, Fangfang Qu, Pengcheng Nie

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Predicted distribution of Metaparasitylenchus hypothenemi (Tylenchida: Allantonematidae), parasite of the coffee berry borer by Simota-Ruiz M., Castillo A., Cisneros-Hernández J., Carmona-Castro O.

“…The geographical distribution of this parasite was predicted based on current data, using geographical information systems (GIS), the MaxEnt algorithm, and historical data to improve the prediction accuracy for other Neotropical regions. …”
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Transmission Line Icing Prediction Based on Physically Guided Fast-Slow Transformer by Feng Wang, Ziming Ma

“…Finally, the sample mixing enhancement algorithm is used to reduce the overfitting problem and improve the generalization performance of the prediction model. …”
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Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments by Liangtao Xu, Shuang Chen, Wen Yao

“…Over nearly three rainy seasons of lightning activity in North China, numerical prediction experiments were carried out using the Weather Research and Forecasting model coupled with electrification and discharge schemes (WRF-Electric). …”
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Protein function prediction using GO similarity-based heterogeneous network propagation by Sai Hu, Bihai Zhao

“…Abstract Protein function prediction is a fundamental cornerstone in bioinformatics, providing critical insights into biological processes and disease mechanisms. …”
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MRI Biomarkers for Hand-Motor Outcome Prediction and Therapy Monitoring following Stroke by U. Horn, M. Grothe, M. Lotze

“…Several biomarkers have been identified which enable a considerable prediction of hand-motor outcome after cerebral damage already in the subacute stage after stroke. …”
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Radiomics analysis for prediction and classification of submucosal tumors based on gastrointestinal endoscopic ultrasonography by Hui Zhou, Guoliang Wei, Junke Wu

“…It can be used for personalized and non‐invasive prediction of the type of submucosal tumors, providing physicians with aid for early treatment and management of tumor progression.…”
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Energy Consumption Prediction Model for Electric Buses Considering Actual Quantifiable Features by Guowei Zhu, Miao Shi, Jia He

“…The new prediction model is essentially a machine learning model based on k-means clustering algorithm, which leverages feature extraction and data analysis to make predictions. …”
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Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

“…Due to new online shopping trends over the internet, the seller needs to predict the online customer’s choice. This field is a new area of research for machine learning researchers. …”
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Integration of RSM and Machine Learning for Accurate Prediction of Surface Roughness in Laser Processing by Dragan Rodić, Milenko Sekulić, Borislav Savković, Miloš Madić, Milan Trifunović

“…Although the RSM model achieved an R² value of 0.8227, there were still some nonlinear deviations between the predicted and experimental values. To improve the prediction accuracy, a regression tree algorithm was applied to model the residuals of the RSM output. …”
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Aerodynamic Prediction and Design Optimization Using Multi-Fidelity Deep Neural Network by Bingchen Du, Ennan Shen, Jiangpeng Wu, Tongqing Guo, Zhiliang Lu, Di Zhou

“…As the insufficiency in the prediction accuracy of the optimal shapes appears when employing the non-updated MFDNN models, an update strategy is developed by tightly integrating the MFDNN models with the particle swarm optimization algorithm. …”
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Artificial intelligence in predicting pathogenic microorganisms’ antimicrobial resistance: challenges, progress, and prospects by Yan Li, Xiaoyan Cui, Xiaoyan Yang, Guangqia Liu, Juan Zhang

“…Furthermore, we explore the major challenges in the field, such as data availability, model interpretability, and cross-species resistance prediction. Finally, we discuss new perspectives and solutions for research into microbial resistance through algorithm optimization, dataset expansion, and interdisciplinary collaboration. …”
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Vehicle Trajectory Prediction Using Residual Diffusion Model Based on Image Information by Wei He, Haoxuan Li, Tao Wang, Nan Wang

“…In automatic driving, accurate prediction of vehicle trajectory is the key to achieve automatic driving, and multi-vehicle joint trajectory prediction has become an important part of modern human-computer interaction systems such as automatic driving. …”
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The Effect of Temperature on Intestinal Flora Imbalance Based on Time Series Prediction Model by Jing Zhu, Yafei Xue, Shuyuan Yang

“…The effects of air factors and carbon dioxide content on the prediction results are evaluated by statistical analysis. …”
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Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…Cognitive impairment is a common non-motor symptom of Parkinson's disease (PD), significantly affecting patients' quality of life and posing challenges for clinical management. Early prediction of cognitive decline in PD is critical for timely diagnosis and intervention. …”
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Surface Roughness Prediction of Bearing Ring Precision Grinding Based on Feature Extraction by Chaoyu Shi, Bohao Chen, Yao Shi, Jun Zha

“…In order to improve the surface roughness of bearing ring grinding under multiple working conditions, a prediction model of bearing ring surface roughness based on feature extraction was proposed. …”
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Integration of SimWeight and Markov Chain to Predict Land Use of Lavasanat Basin by M S. Mirakhorlo, M. Rahimzadegan

“…Production and prediction of land-use/land cover changes (LULCC) map are among the significant issues regarding input of many environmental and hydrological models. …”
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Predicting patient deterioration with physiological data using AI: systematic review protocol by Chris Plummer, Edward Meinert, Victoria Riccalton, Lynsey Threlfall, Cen Cong

“…This systematic review aims to establish which AI or machine learning algorithm is best suited to analysing physiological data sets to predict patient deterioration in a hospital setting.Methods and analysis A systematic review will be conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) and the PICOS (Population, Intervention, Comparator, Outcome and Study) frameworks. …”
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Data efficient prediction of excited-state properties using quantum neural networks by Manuel Hagelueken, Marco F Huber, Marco Roth

“…We present a quantum machine learning model that predicts excited-state properties from the molecular ground state for different geometric configurations. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

“…We introduce the Resource-Aware Adaptive Decision Algorithm (RAADA), which leverages reinforcement learning to translate SADF-Net’s predictions into optimized strategies for resource allocation, such as irrigation scheduling and pest control. …”
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