Slope deformation prediction based on GA–BP neural networks by Wenhui TAN, Kai LI, Huimin LIU, Meifeng CAI, Qifeng GUO

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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. …”
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Denoising MEMS accelerometer sensors based on L2‐norm total variation algorithm by R. Abbasi‐Kesbi, A. Nikfarjam

“…By benefiting from the LTV algorithm, the obtained signals from the accelerometer are denoised. …”
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Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems bi... by M. R. P. De Silva, J. W. J. K. Weeraman, S. Piyatissa, P. C. Fernando

“…Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. …”
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DEVELOPING PREDICTIVE MODELS OF INTERNET SERVICE STRATEGIES by Maxim Yu. Khramov

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Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model by Yi Zhang, Pengtao Liu, Yingying Xu, Meng Zhang

Subjects: “…Swarm intelligence optimization algorithm…”
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Endpoint carbon content and temperature prediction model in BOF steelmaking based on posterior probability and intra-cluster feature weight online dynamic feature selection by Wang Haodong, Liu Hui, Chen FuGang, Li Heng, Xue XiaoJun

“…A posterior probability and intra-cluster feature weight online dynamic feature selection algorithm is proposed to address the issues of high dimensionality and high volatility of data in the basic oxygen furnace (BOF) steelmaking production process. …”
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Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods by Pravin Arun Sawant, Sakshi Shantanu Hiralkar, Yogita Purushottam Hulsurkar, Mugdha Sharad Phutane, Uma Satish Mahajan, Abhay Machindra Kudale

“…METHODS The features of OTC antibiotic use were selected using stepwise logistic, lasso, random forest, XGBoost, and Boruta algorithms. Regression and tree-based models with all confirmed and tentatively important features were built to predict the use of OTC antibiotics. …”
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EfficientNet-b0-Based 3D Quantification Algorithm for Rectangular Defects in Pipelines by Di Wu, Yong Hong, Jie Wang, Shaojun Wu, Zhihao Zhang, Yizhang Liu

“…This multi-task learning model utilizes a shared feature extraction layer and numerous branching networks to create individual predictions for each task: length, width, and depth. …”
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Optimization Design of Multi-Blade Centrifugal Fan Based on Variable Weight PSO-BP Prediction Model and Multi-Objective Beluga Optimization Algorithm by Wenyang Jin, Jiaxuan Wang, Junyu Li, Ren Xu, Ming Zhou, Qibai Huang

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Optimizing Bifacial Solar Modules with Trackers: Advanced Temperature Prediction Through Symbolic Regression by Fabian Alonso Lara-Vargas, Carlos Vargas-Salgado, Jesus Águila-León, Dácil Díaz-Bello

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Development and indirect validation of a model predicting frailty in the French healthcare claims database by Hana Lahbib, Laurence Mandereau-Bruno, Sarah Goria, Vérène Wagner, Marion J Torres, Catherine Féart, Catherine Helmer, Karine Pérès, Laure Carcaillon-Bentata

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Balancing accuracy and convergence rate: a hybrid optimisation algorithm for parameter identification of unmanned marine vehicles by Zheng Li, Caoyang Yu, Yiming Zhong, Yuanju Cao, Xianbo Xiang, Lian Lian

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Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

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Predicting Student Performance and Enhancing Learning Outcomes: A Data-Driven Approach Using Educational Data Mining Techniques by Athanasios Angeioplastis, John Aliprantis, Markos Konstantakis, Alkiviadis Tsimpiris

“…This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. …”
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Epistemic authority and generative AI in learning spaces: rethinking knowledge in the algorithmic age by Binny Jose, Anu Cleetus, Bindhu Joseph, Lumy Joseph, Benymol Jose, Amruth K. John

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Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments by Hanspeter Hess, Alexandra Oswald, J. Tomás Rojas, Alexandre Lädermann, Matthias A. Zumstein, Kate Gerber

“…A deep learning-based segmentation network was trained with paired CT derived scapula segmentations. An algorithm to fuse multi-plane segmentations was developed to generated high-resolution 3D models of the scapula on which morphological landmark- and axes were predicted using a second deep learning network for morphological analysis. …”
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Establishment of predictive models for postoperative delirium in elderly patients after knee/hip surgery based on total bilirubin concentration: machine learning algorithms by Shuhui Hua, Chuan Li, Yuanlong Wang, YiZhi Liang, Shanling Xu, Jian Kong, Hongyan Gong, Rui Dong, Yanan Lin, Xu Lin, Yanlin Bi, Bin Wang

“…In addition, the SHAP method determines that age and education are the main determinants that affect the prediction of ML models. …”
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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

“…However, studies focusing the spatial prediction of geophysical data remain limited. In this research, we aimed to model and predict the spatial distribution of soil geophysical properties using parent material and terrain attributes with machine learning algorithms. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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