Prediction Method and Characteristics of Static Acoustic Scattering for Marine Composite Propellers by Suchen XU, Zilong PENG, Fulin ZHOU, Xuhong MIU, Huicheng KE

“…This study introduces a hybrid approach to predict the acoustic scattering characteristics of composite propellers featuring variable thickness and complex curvature. …”
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Predicting Future Intrablock Links in Directed Networks Using Triadic Patterns by Lekshmi S. Nair, J. j

“…Directed multilayer networks are used to represent such networks effectively, capturing the heterogeneity exhibited by the nodes and the directionality of relationships. The link prediction problem refers to predicting relationships (links) between the entities (nodes) that may arise in the future or identifying missing links to reconstruct the network. …”
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SOIL MOISTURE PREDICTION MODEL IN PEATLAND USING RANDOM FOREST REGRESSOR by Helda Yunita Taihuttu, Imas Sukaesih Sitanggang, Lailan Syaufina

“…For this reason, this study aims to create a prediction model for soil moisture as an early prevention of fires in peatlands using the Random Forest Regressor (RFR) algorithm. …”
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The Influential Factors and Prediction of Kuroshio Extension Front on Acoustic Propagation-Tracked by Weishuai XU, Lei ZHANG, Hua WANG

“…This study employed a backpropagation neural network to predict the acoustic propagation affected by the KEF. …”
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Distributed Target Detection with Coherent Fusion in Tracking Based on Phase Prediction by Aoya Wang, Jing Lu, Shenghua Zhou, Linhai Wang

“…From historic observations on target tracking, relative phase delays in different channels are predicted by a phase lock loop and then used to compensate phases for observations in the current frame. …”
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Factors Identification and Prediction for Mind Wandering Driving Using Machine Learning by Ciyun Lin, Hongli Zhang, Bowen Gong, Dayong Wu

“…The aim of this study was to propose a framework for analyzing and predicting MW based on readily available driving status data. …”
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Quantum Perceptron in Predicting the Number of Visitors to E-Commerce Websites in Indonesian by Solikhun Solikhun, Dinda Carissa Arishandy, Ela Roza Batubara, Poningsih

“…The research results show that the Quantum Perceptron algorithm can make predictions very well compared to the classical perceptron, proven by the Quantum Perceptron having a perfect accuracy of 100% with a total of 2 epochs while the classical perceptron has 100% accuracy with a total of 10 epochs. …”
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Predicting for mortality rate using regression analysis in patient with burn injury by O. O. Zavorotniy, E. V. Zinoviev, D. V. Kostyakov

“…The final algorithm included 18 predictors. The model allows predicting a positive outcome of treatment and the likelihood of a fatal outcome with an accuracy of 93 and 87 % respectively.Conclusion. …”
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Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox by Quanbo Lu, Mei Li, Xiaojuan Huang

“…To further improve prediction accuracy, the paper employs the Central Particle Swarm Optimization algorithm to merge both theoretical and actual RUL values. …”
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RUL prediction method based on cross-view hybrid network model by Ai Yandi, Fang Dong, Tian Zhiping, Yan Kaiyang

“…Secondly, a RUL regression algorithm integrating Transformer encoder and nonlinear fitter is developed to automatically learn the correlation between features in different views and predict RUL. …”
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Curing simulation and data-driven curing curve prediction of thermoset composites by Chenchen Wu, Ruming Zhang, Pengyuan Zhao, Liang Li, Dingguo Zhang

“…Then, the temperature–time and the resulting degree-of-cure-time curves obtained from finite element simulations were created for training the prediction models using machine learning approaches of support vector regression (SVR), back propagation (BP) neural network and BP neural network optimized by genetic algorithm (GA-BP). …”
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RUL Prediction Based on MBGD-WGAN-GRU for Lithium-Ion Batteries by Zhiguo Zhao, Ke Li, Yibo Dai, Biao Chen, Yeqin Wang, Qian Zhao

“…To address the challenges associated with acquiring complete charge-discharge cycle data and extracting health indicator factors (IHFs) from fragmented datasets in current automotive lithium-ion batteries (LIBs), this study proposes a novel online remaining useful life (RUL) prediction method. First, the IHF, which captures battery aging characteristics, is extracted from raw LIBs data, and the dataset is partitioned into training (70%) and testing (30%) subsets. …”
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Machine learning-based prediction of LDL cholesterol: performance evaluation and validation by Jing-Bi Meng, Zai-Jian An, Chun-Shan Jiang

“…Objective This study aimed to validate and optimize a machine learning algorithm for accurately predicting low-density lipoprotein cholesterol (LDL-C) levels, addressing limitations of traditional formulas, particularly in hypertriglyceridemia. …”
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Metasurface-Based Solar Absorption Prediction System Using Artificial Intelligence by Md. Mottahir Alam, Ahteshamul Haque, Asif Irshad Khan, Samir Kasim, Amjad Ali Pasha, Aasim Zafar, Kashif Irshad, Anis Ahmad Chaudhary, Md. Samsuzzaman, Rezaul Azim

“…Moreover, Golden Eagle Optimization (GE)-based deep AlexNet algorithm is proposed for predicting the parameter variation and their effect on absorbance. …”
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Enhancing freight train delay prediction with simulation‐assisted machine learning by Niloofar Minbashi, Jiaxi Zhao, C. Tyler Dick, Markus Bohlin

“…Additionally, utilization rates—except for the receiving yard—enhance the predictions.…”
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Artificial neural networks in predicting impaired bone metabolism in diabetes mellitus by S. S. Safarova

“…The ANN model was trained by optimizing the relationship between a set of input data (a number of clinical and laboratory parameters: gender, age, body mass index, duration of diabetes mellitus, etc.) and a set of corresponding output data (variables reflecting the state of bone metabolism: bone mineral density, markers of bone remodeling).Results. The ANN-based algorithm predicted estimated values of bone metabolism parameters in the examined individuals by generating output data using deep learning. …”
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Demand Prediction of Railway Emergency Resources Based on Case-Based Reasoning by Jianping Sun, Hantao Cao, Biao Geng, Zhaoping Tang, Xiaopeng Li

“…The demand prediction of emergency resources is helpful for rational allocation and optimization of emergency resources for railway rescue when emergency incident occurs. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…Abstract Accurate prediction of vehicle maintenance demands is crucial for sustaining vehicle use, optimizing performance, and minimizing ownership costs. …”
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Cosmological Prediction of the Void and Galaxy Clustering Measurements in the CSST Spectroscopic Survey by Yingxiao Song, Qi Xiong, Yan Gong, Furen Deng, Kwan Chuen Chan, Xuelei Chen, Qi Guo, Guoliang Li, Ming Li, Yun Liu, Yu Luo, Wenxiang Pei, Chengliang Wei

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Data-driven prediction of cardiovascular and cerebrovascular diseases in a nationwide study by Sehyun Kim, Beomsang Ryu, Mingee Choi, Sangyon Lee, Jaeyong Shin, Sok Chul Hong

“…The logistic regression model incorporating variables selected by the LASSO algorithm exhibited superior predictive performance relative to other models, although the differences were not statistically significant. …”
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