Electromechanical Battery EMB Mass Minimization taking into Account its Electrical Machines Rotor Energy by Podgornovs Andrejs, Sipovichs Antons

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Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

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Prediction Models for Diabetes in Children and Adolescents: A Review by Livija Cveticanin, Marko Arsenovic

“…Newly identified factors for differentiating between types of diabetes are discussed, alongside an overview of various machine learning and deep learning algorithms specifically adapted for diabetes prediction in children and adolescents. …”
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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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Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction by Jinyang Dai

“…Combining the advantages of three data-driven prediction algorithms, namely, random forest, extreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT), a model based on improved random forest algorithm is proposed. …”
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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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Online English Teaching Course Score Analysis Based on Decision Tree Mining Algorithm by Xiaojun Jiang

“…In this paper, we use the global search advantage of genetic algorithm to build a GABP hybrid prediction model to solve the local minimum problem of BP neural network algorithm. …”
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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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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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