Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…In this study, a novel machine learning-based predictive approach was proposed to improve port operations by accurately forecasting vessel waiting times. …”
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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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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. This approach results in the development of an earthquake casualty prediction model based on PCA-BO-SVM. …”
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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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A nomogram for predicting small bowel mucosal healing in pediatric Crohn’s disease by Bingxia Chen, Huiwen Li, Hongli Wang, Lu Ren, Liya Xiong, Yang Cheng, Rui Li, Meiwan Cao, Zihuan Zeng, Sitang Gong, Peiyu Chen, Lanlan Geng

“…The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was applied to identify predictive factors for small bowel MH. …”
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Prediction of rock burst risk in underground openings based on intuitionistic fuzzy set by Xin Wang, Kebin Shi, Quan Shi, Heng Zhang, Liqiang Bai

“…In this paper, a model for risk prediction of rock burst is proposed based on intuitionistic fuzzy set theory. …”
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Multi-feature stock price prediction by LSTM networks based on VMD and TMFG by Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…Finally, the filtered features are modeled and predicted using a Long Short-Term Memory (LSTM) network. …”
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Neural network for prediction solar radiation in Relizane region (Algeria) - Analysis study by Dahmani Abdennasser, Yamina Ammi, Salah Hanini

“…The global solar radiation prediction is the most necessary part of the project and performance of solar energy applications. …”
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Recurrence Multilinear Regression Technique for Improving Accuracy of Energy Prediction in Power Systems by Quota Alief Sias, Rahma Gantassi, Yonghoon Choi, Jeong Hwan Bae

“…This paper also creates a pre-clustering using the K-Means algorithm before the energy prediction to improve accuracy. …”
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Application of phase analysis to predict long-term dynamics of atmospheric air temperature by L.  T. Sozaeva

“…Further prediction of the values of the time series in the retrospective section is carried out by the least square method. …”
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Deep spatio-temporal dependent convolutional LSTM network for traffic flow prediction by Jie Tang, Rong Zhu, Fengyun Wu, Xuansen He, Jing Huang, Xianlai Zhou, Yishuai Sun

“…Secondly, for time features, most scholars use time series prediction models, such as recurrent neural networks and their variants. …”
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Rockburst Prediction Based on the KPCA-APSO-SVM Model and Its Engineering Application by Yuefeng Li, Chao Wang, Jiankun Xu, Zonghong Zhou, Jianhui Xu, Jianwei Cheng

“…The comparative results show that the KPCA-APSO-SVM model has a higher prediction accuracy; as such, it provides a new reliable method for rockburst prediction.…”
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Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction by Jamal Abdulrazzaq Khalaf, Abeer A. Majeed, Mohammed Suleman Aldlemy, Zainab Hasan Ali, Ahmed W. Al Zand, S. Adarsh, Aissa Bouaissi, Mohammed Majeed Hameed, Zaher Mundher Yaseen

“…Accurate and reliable prediction of Perfobond Rib Shear Strength Connector (PRSC) is considered as a major issue in the structural engineering sector. …”
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