A Multi-Fusion Early Warning Method for Vehicle–Pedestrian Collision Risk at Unsignalized Intersections by Weijing Zhu, Junji Dai, Xiaoqin Zhou, Xu Gao, Rui Cheng, Bingheng Yang, Enchu Li, Qingmei Lü, Wenting Wang, Qiuyan Tan

Subjects: “…pedestrian trajectory prediction…”
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Retracted: Intelligent Recommendation Algorithm of Multimedia English Distance Education Resources Based on User Model by Journal of Mathematics

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Validation of a teaching model instrument for university education in Ecuador through an artificial intelligence algorithm by Jenniffer Sobeida Moreira-Choez, Tibisay Milene Lamus de Rodríguez, Aracelly Fernanda Núñez-Naranjo, Ángel Ramón Sabando-García, María Belén Reinoso-Ávalos, Cynthia Michel Olguín-Martínez, Daniel Omar Nieves-Lizárraga, Julieta Elizabeth Salazar-Echeagaray

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ALGORITHM FOR MASTERING THE PROCESS OF SKETCHES AND DRAFTS OF THE HUMAN FIGURE FOR STUDENTS OF HIGHER EDUCATION IN ART SPECIALTIES by І. Гуржій, Д. Коршунов

“…In the future, the problem of integrating the educational components "Drawing" and "Plastic Anatomy" requires research attention.…”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Through comprehensive evaluation using both synthetic and real-world traces from deep learning training workloads, our method demonstrates substantial improvements over state-of-the-art algorithms: achieving up to 45.1% reduction in average I/O latency, 32.5% improvement in throughput for critical applications, and 28.8% reduction in storage costs. …”
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Predictive Analysis of Cardiovascular Disease Risk Factors in Romania using Machine Learning and Medical Statistics by Radu-Anton MOLDOVAN, Sebastian-Aurelian ŞTEFĂNIGĂ

“…Based on our findings, a series of preventive interventions and policy recommendations for cardiovascular risk reduction at the individual and population levels can be implemented. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…These parameters feed into the digital twins, further refining the predictive and diagnostic capabilities of the models. …”
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MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW by Armand Florin Bertea, Cezar Honceriu

“…Machine learning has numerous applications in sports, which mainly aim at anticipating medical problems and the recovery potential of athletes, predicting the results of sporting events, estimating how different elements of a match can influence its outcome, assessing the market value of a player, and predicting the performance of young players. …”
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Prediction of Influence of Environmental Factors on the Toxicity of Pentachlorophenol on <i>E. coli</i>-Based Bioassays by Sulivan Jouanneau, Gerald Thouand

“…This study addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxicant, pentachlorophenol (PCP). …”
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Correction of Disturbances Influence on Results of Elongated Objects's Probe Microscopy Using Predictive Relief Estimates by P. V. Gulyaev

“…The peculiarity of predictive images is the sharpening of areas distorted by disturbances. …”
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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity... by Yanli Yao, Yu Li, Yulan Chen, Xuan Qiu, Gulimire Aimaiti, Ayiguzaili Maimaitimin

“…A comprehensive analysis utilizing the random forest machine learning algorithm demonstrated that the AHI exhibits the highest predictive value. …”
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An Educational Approach to Higgs Boson Hunting Using Machine Learning Classification Algorithms on ATLAS Open Data by Ayşe Bat

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Decoding student cognitive abilities: a comparative study of explainable AI algorithms in educational data mining by Tianyue Niu, Ting Liu, Yiming Taclis Luo, Patrick Cheong-Iao Pang, Shuaishuai Huang, Ao Xiang

Subjects: “…Educational data mining…”
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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

“…The goal of this research is to first develop an accurate ensemble model for prediction of unseen cases of CKD given the biomarkers. …”
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A multifaceted comparative analysis of incremental dynamic and static pushover methods in bridge structural assessment, integrated with artificial neural network and genetic algori... by Ashwini Satyanarayana, V. Sindura, L. Geetha, Rakesh Kumar, Mohd Asif Shah, Mary Subaja Christo

“…The results of static pushover analysis and incremental dynamic analysis (IDA) are predicted and compared in this work using ANN and GA, which offers a deeper understanding of their predictive capabilities.…”
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Predictive direct control strategy of unified power quality conditioner based on power angle control by Guifeng Wang, Zewen Wu, Zhan Liu

“…This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. …”
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Machine Learning and Multilayer Perceptron-Based Customized Predictive Models for Individual Processes in Food Factories by Byunghyun Lim, Dongju Kim, Woojin Cho, Jae-Hoi Gu

“…Additionally, it proposes a customized predictive model employing four machine learning algorithms—linear regression, decision tree, random forest, and k-nearest neighbor—as well as two deep learning algorithms: long short-term memory and multi-layer perceptron. …”
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Sizing and Characterization of Load Curves of Distribution Transformers Using Clustering and Predictive Machine Learning Models by Pedro Torres-Bermeo, Kevin López-Eugenio, Carolina Del-Valle-Soto, Guillermo Palacios-Navarro, José Varela-Aldás

“…The results show that DTW with K-means provides the best segmentation, with a cross-correlation similarity of 0.9552 and a temporal consistency index of 0.9642. For predictive modeling, supervised algorithms were tested, where Random Forest achieved the highest accuracy in predicting the corresponding load curve type for each transformer (0.78), and the SVR model provided the best performance in predicting the maximum load, explaining 90% of the load variability (R² = 0.90). …”
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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Nevertheless, enhancing boosting algorithms to achieve superior predictive accuracy continues to be a difficult task. …”
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