Towards Predicting Basketball Player Positions with Transformative Insights by Angelos Tsiannis, Christodoulos Efstathiades

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Coupling of green building construction based on particle Swarm optimizing neural network algorithm by Wang Leigang, Li Shaohua, Wang Liang, Zhang Zheng, Zhou Yuchen, Chang Long

“…Compared with traditional methods, the prediction error of this algorithm is significantly reduced, and the data fitting accuracy is improved to 0.99809, indicate its effectiveness in predicting construction safety risks. …”
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RAFFLE: active learning accelerated interface structure prediction by Ned Thaddeus Taylor, Joe Pitfield, Francis Huw Davies, Steven Paul Hepplestone

“…Abstract Interfaces between materials are critical to the performance of many devices, yet predicting their structure is computationally demanding due to the vast configuration space. …”
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Model Predictive Control Used in Passenger Vehicles: An Overview by Meaghan Charest-Finn, Shabnam Pejhan

“…The following article presents a high-level overview of how Model Predictive Control (MPC) is leveraged in passenger vehicles and their subsystems for improved performance. …”
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Informing Disaster Recovery Through Predictive Relocation Modeling by Chao He, Da Hu

“…This study explores the use of machine learning algorithms to improve the prediction of household relocation in the aftermath of disasters. …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“…The findings illustrate that RFR is achieving better performance than the other two algorithms, as the predicted magnitudes are close to the actual magnitudes. …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…The difference between the predicted and actual future spatial population values using the proposed algorithm was less than 2%, which was 56.5% lower than the other two prediction algorithms on average. …”
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Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains by Jie Zhang, Junnan He, Shihao Ren, Pei Zhou, Jun Guo, Mingyue Song

“…Through simulation experiments, the proposed Improved Genetic Algorithm (IGA) achieved an average rescue time reduction of 8.5% compared to conventional Genetic Algorithm (GA) and 3.5% compared to Improved Artificial Bee Colony (IABC) algorithm, with an average solution time of 9.4 ms.…”
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Improving data processing in medical education through machine learning by N. Shyndaliyev, A. Orynbayeva, K. Shadinova, A. Barakova, N. Nurmukhanbetova

“…This study contributes to the growing body of literature advocating for ML integration in medical education and underscores the need for further research into advanced ML algorithms and long-term clinical outcomes.…”
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Advances in Video Emotion Recognition: Challenges and Trends by Yun Yi, Yunkang Zhou, Tinghua Wang, Jin Zhou

“…Video emotion recognition (VER), situated at the convergence of affective computing and computer vision, aims to predict the primary emotion evoked in most viewers through video content, with extensive applications in video recommendation, human–computer interaction, and intelligent education. …”
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Machine learning-driven condition monitoring for predictive maintenance by Mahliyo Aliyeva

“…ML algorithms, including Artificial Neural Networks and Random Forest Regression, enable the proactive forecasting of impending failures by constructing data-centric thermal models tailored for power electronics modules, thus averting catastrophic malfunctions such as air outlet blockages. …”
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Proactive Edge Caching With Popularity Prediction and Content Replication by Ilhan Demirci, Omer Korcak

“…The algorithm incorporates both global and local content popularity predictions—obtained via exponential moving average (EMA) and long short-term memory (LSTM) models, and dynamically scales content placement decisions based on delay-aware replication benefits. …”
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Wineinformatics: Wine Score Prediction with Wine Price and Reviews by Yuka Nagayoshi, Bernard Chen

“…The goal of this paper is to determine whether incorporating wine price can improve the accuracy of score prediction. To explore the relationship between wine price and wine score, naive Bayes classifier and support vector machine (SVM) classifier are employed to predict the scores as either equal to or above 90 or below 90. …”
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Evaluating the Predictive Power of Software Metrics for Fault Localization by Issar Arab, Kenneth Magel, Mohammed Akour

“…We fitted thousands of models and benchmarked different algorithms—including deep learning, Random Forest, XGBoost, and LightGBM—to choose the best-performing model. …”
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Rapid Colorectal Tissue Classification Using Data-Driven Raman Techniques by Jakub Tomes, Daniela Janstova, Shayestegan Mohsen, Alla Sinica, Zuzana Kovacova, Jaromir Petrtyl, Jan Mares

“…Various machine-learning algorithms have been evaluated for classification, including Long Short-Term Memory (LSTM), Multi-Layer Perceptron (MLP), and Extreme Gradient Boosting (XGBoost), and hybrid supervised-unsupervised methods involving dimensionality reduction, clustering, and classification. …”
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Aberrant gene expression prediction across human tissues by Florian R. Hölzlwimmer, Jonas Lindner, Georgios Tsitsiridis, Nils Wagner, Francesco Paolo Casale, Vicente A. Yépez, Julien Gagneur

“…Abstract Despite the frequent implication of aberrant gene expression in diseases, algorithms predicting aberrantly expressed genes of an individual are lacking. …”
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Predictive analysis of doubly Type-Ⅱ censored models by Young Eun Jeon, Yongku Kim, Jung-In Seo

“…Second, it addresses prediction problems in a closed-form manner, ensuring computational efficiency. …”
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Machine Learning‐Assisted Simulations and Predictions for Battery Interfaces by Zhaojun Sun, Xin Li, Yiming Wu, Qilin Gu, Shiyou Zheng

“…By employing ML algorithms and machine vision, simulations of lithium dendrite growth, SEI formation, and interfacial dynamics can be performed. …”
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Prediction and evaluation of residual life of casing with corrosion defects by JIA Aoyin, QIAN Liqin, WANG Jie, YANG Jingwei, WU Yaokun, WEI Mingji

“…The particle swarm optimization-gaussian process regression （PSO-GPR) algorithm was employed to construct a predictive model for casing corrosion rates.ResultsIntegration of the two models, the evaluation of the residual life of casings with corrosion defects was completed, it has theoretical guidance significance for the prevention and management of corroded casings in oil field operations.…”
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Predicting the performance of ORB-SLAM3 on embedded platforms by Jacques Matthee, Kenneth Uren, George van Schoor, Corne van Daalen

“…Therefore, a need exists to  evaluate the performance of SLAM algorithms in practical embedded environments – this paper addresses this need by creating  prediction models to estimate the performance that ORB-SLAM3 can achieve on embedded platforms. …”
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