Accurate Rotor Temperature Prediction of Permanent Magnet Synchronous Motor in Electric Vehicles Using a Hybrid RIME-XGBoost Model by Jianzhao Shan, Zhongyuan Che, Fengbin Liu

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Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme by Tianrui Ye, Wenhao Gui

Subjects: “…expectation–maximization algorithm…”
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Short-term Price Prediction in Initial Public Offerings Using XGBoost: Bist Technology Sector Example by Ayse Merve Acılar, Gamze Şekeroğlu

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Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun, Kun Yang

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Mathematics in the streets and in schools by Pouya Karimi, Abolfazl Rafiepour

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Early stage prediction of bone regeneration using FEA and cell differentiation algorithms with 3D-printed PLA and PCL scaffolds: modeling and application to dorsal double-plating in distal radius fractures by Hsuan Chih Liu, Ya-Han Chan, Shao-Fu Huang, Wei-Che Tsai, Yen Cheng, Chun-Li Lin

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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

“…There are many influencing factors and difficulty in the prediction of total organic carbon content, so it is particularly important to explore the most suitable high-precision prediction method for the prediction of total organic carbon content in this area. …”
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Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP by Shuang Liu, Enxiang Qu, Chun LV, Xueyuan Zhang

“…Compared with the unoptimized BP neural network and the BP neural network optimized by the artificial bee colony algorithm (ABC) model, this model has higher prediction accuracy and is more suitable for predicting the blasting block size of open-pit coal mines, it provides a new method for predicting the fragmentation of blasting under the influence of multiple factors, filling the gap in related theoretical research, and has certain practical application value.…”
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A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

“…Our results highlight the long short-term memory (LSTM) algorithm’s robustness achieving the highest accuracy of 94% and an F1-score of 0.87 along with a support vector machine (SVM), indicating high efficacy in predicting student success at the onset of learning coding. …”
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Hybrid statistical-algorithmic approach using the frog algorithm to optimize blast patterns for reducing blast vibrations by Abbas Khajouei Sirjani, Farhang Sereshki, Mohammad Ataei, Manoj Khandelwal, Hojatollah Mohammadi Anayi, Seyed Mohammad Mehdi Mousavi Nasab, Mohammad Amiri Hosseini

“…This study introduces an innovative approach to predict and mitigate blast-induced vibrations by optimizing blast patterns. …”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

Subjects: “…Photovoltaic power prediction…”
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Learning path planning methods based on learning path variability and ant colony optimization by Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao

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KPLS Optimization With Nature-Inspired Metaheuristic Algorithms by Jorge Daniel Mello-Roman, Adolfo Hernandez

“…It was solved using nature-inspired metaheuristic algorithms: the genetic algorithm, particle swarm optimization, grey wolf optimization and the firefly algorithm. …”
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Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…Deep-learning neural networks optimized with the Levenberg-Marquardt algorithm (DLNNs-LMA) is a supervised AI-based approach that is used to analyze the Eyring Powell fluid in a two-phase flow (EPFM-TPF) with dust particles and at temperature-dependent viscosity. …”
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Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning by Jiayuan Xu, Andrew J. Doig, Sofia Michopoulou, Sofia Michopoulou, Petroula Proitsi, Petroula Proitsi, Fumie Costen, The Alzheimer's disease neuroimaging initiative

“…This study aims to develop and validate machine learning algorithms for accurately predicting brain Aβ positivity using plasma biomarkers, genetic information, and clinical data as a cost-effective alternative to PET imaging.MethodsWe analyzed 1,043 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and validated our models on 127 patients from the Center for Neurodegeneration and Translational Neuroscience (CNTN) dataset. …”
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Development and validation of a CT algorithm based on intratumoral necrosis and tumor morphology to predict the nuclear grade of small (2–4 cm) solid clear cell renal cell carcinoma by Jianyi Qu, Pingyi Zhu, Xianli Zhu, Xinyan Li, Wenjie Zhang, Xinhong Song, Xiaofei Wang, Chenchen Dai, Qianqian Zhang, Jianjun Zhou

“…The study aimed to develop and validate a CT algorithm for the prediction of the WHO/ISUP nuclear grade of small (2–4 cm) solid ccRCC. …”
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Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study by Bin Zhao, Jin Shang, Xiaoxue Zhang

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Maintenance Time Prediction for Predictive Maintenance of Ship Engines by Seunghun Lim, Jungmo Oh, Jinkyu Park

“…However, due to the nature of ship operation, data collection is difficult, and most studies focus on fault detection, hindering the application of predictive maintenance to ships. In this study, we developed a maintenance time prediction algorithm using the revision generator engine condition criterion (RGCCV) value and the cylinder exhaust gas temperature, as developed in a previous study for marine generator engines. …”
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Multipath Estimation of Navigation Signals Based on Extended Kalman Filter–Genetic Algorithm Particle Filter Algorithm by Jie Li, Xiyan Sun, Yuanfa Ji, Jingjing Li, Long Li

“…This method utilizes the EKF to calculate the mean and covariance of samples using the latest observation information, providing a more reasonable proposal density for particle filtering and enhancing the accuracy of state prediction. Simultaneously, by introducing the crossover and mutation mechanisms of the adaptive genetic algorithm, particles are continuously evolved during the resampling process, preventing them from falling into local extrema. …”
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Research on parameter selection and optimization of C4.5 algorithm based on algorithm applicability knowledge base by Yiyan Zhang, Yi Xin, Qin Li

“…Abstract Given that the decision tree C4.5 algorithm has outstanding performance in prediction accuracy on medical datasets and is highly interpretable, this paper carries out an optimization study on the selection of hyperparameters of the algorithm in order to achieve fast and accurate optimization of the algorithm model. …”
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