A Fourfold Bi-Filter and Permuted Bi-Quad-Wrapper Feature Selection Method for Finding Optimal Moments of Multi-Trajectory Transient Records in Transient Analysis by Seyed Alireza Bashiri Mosavi, Omid Khalaf Beigi

“…Finally, the efficacy of OTMs survived by the F2FP2QW model in TA is evaluated via a cross-validation scenario. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…These models were compared using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) in order to distinguish the APQC model from the other available models. …”
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Quantification of Argan Oil (<i>Argania spinosa</i> L.) Adulterated with Avocado, Flaxseed, Walnut, and Pumpkin Oils Using Fourier-Transform Infrared Spectroscopy and Advanced Chem... by Linda Gjonaj, Oliver B. Generalao, Arnold Alguno, Roberto Malaluan, Arnold Lubguban, Gerard G. Dumancas

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Leveraging Large Language Models for Predicting Postoperative Acute Kidney Injury in Elderly Patients by Hanfei Zhu, Ruojiang Wang, Jiajie Qian, Yuhao Wu, Zhuqing Jin, Xishen Shan, Fuhai Ji, Zixuan Yuan, Tingrui Pan

“…Impact Statement: Our study demonstrates that LLMs have the potential to address the issues of poor generalization and weak interpretability commonly encountered in disease prediction using traditional machine learning (ML) models. Introduction: AKI is a severe postoperative complication, especially in elderly patients with declining renal function. …”
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Benchmarking of feed-forward neural network models for genomic prediction of quantitative traits in pigs by Junjian Wang, Francesco Tiezzi, Yijian Huang, Christian Maltecca, Jicai Jiang

“…Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. …”
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Development of a model of an electrical complex for gas air cooling devices of gas field №1 gazprom dobycha Yamburg LLC with a centralized power supply system in the MATLAB/SIMULIN... by L. R. Maskov, V. Y. Kornilov

“…The results presented in work are received with use of methods of the theory of electric and magnetic circuits, the theory of electric drive and electric machines, methods of optimization of power supply systems, analytical and numerical methods of applied mathematics, methods of mathematical and computer modeling.RESULTS. …”
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Using the Remote Sensing Method to Simulate the Land Change in the Year 2030 by Burcu Degerli, Mehmet Çetin

“…The predictive values of the LU/LC change that will occur in 2030, calculated with the MLP‑ANN model based on Machine Learning algorithms and mapped with the QGIS 3.16 program. …”
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Assessing the economic impact of climate risk on green and low-carbon transformation by Chen Qin, Hongli Lou, Li Li

“…To bridge this gap, we propose a novel framework that integrates the Integrated Green Transition Model (IGTM) and the Sustainable Transition Optimization Framework (STOF).MethodsIGTM employs agent-based modeling and network dynamics to simulate the cascading impacts of green policies on energy systems and socio-economic outcomes, while STOF leverages advanced optimization and machine learning techniques to balance economic growth, emission reductions, and social equity under diverse scenarios.ResultsBy synthesizing these approaches, our study provides actionable insights into the economic impact of climate risk and offers robust strategies for optimizing investments in renewable energy and policy interventions. …”
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Multi-view fusion of diffusion MRI microstructural models: a preterm birth study by Rosella Trò, Monica Roascio, Domenico Tortora, Mariasavina Severino, Andrea Rossi, Andrea Rossi, Eleftherios Garyfallidis, Gabriele Arnulfo, Gabriele Arnulfo, Marco Massimo Fato, Shreyas Fadnavis

“…Furthermore, we investigated discriminative patterns of preterm birth using multiple analysis methods, drawn from two only seemingly divergent modeling goals, namely inference and prediction. We thus resorted to (i) a traditional univariate voxel-wise inferential method, as the Tract-Based Spatial Statistics (TBSS) approach; (ii) a univariate predictive approach, as the Support Vector Machine (SVM) classification; and (iii) a multivariate predictive Canonical Correlation Analysis (CCA).Main resultsThe TBSS analysis revealed significant differences between preterm and term cohorts in several white matter areas for multiple HARDI features. …”
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Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose by Qiong Zou, Borui Chen, Yang Zhang, Xi Wu, Yi Wan, Changsheng Chen

“…Second, multiple BPNN models were constructed via different variable sets to screen the optimal BPNN. …”
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Data-Driven Customer Retention Strategies in E-Commerce: A Fuzzy Z-Number Approach by Siyin Hu, An Chen

“…For the purpose of evaluating customer churn, we use the Support Vector Machine (SVM) model. In order to improve the performance of the SVM, we tune its parameters using the Coyote Optimization Algorithm (COA). …”
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Strategic Tools for the Formation of Cluster Capital to Implement Technological Innovations by Leyla Gamidullaeva, Nadezhda Shmeleva, Evgeniy Mityakov, Tatyana Tolstykh, Sergey Vasin

“…The application of the proposed model using the example of the PenzaStankoMash industrial machine-building cluster has shown that the optimal configuration of the actors’ capitals in clusters contributes to the creation of synergetic effects. …”
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Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors by Shaofen Huang, Man Luo, Guitong Ye, Zhenlan Yang, Lingling Liao, Nina Wu, Yingting Zhu, Xing Liu, Yehong Zhuo, Hui Xiao

“…The optimal model was further evaluated using 10-fold cross-validation and a validation set. …”
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Prediction of ball mill power in iron ore concentration plants: A comparison between radial basis functions and linear regression by Javad Taghavi, Mahdi Gharabaghi

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Design and Experiment of a Laser Scoring Device for <i>Camellia oleifera</i> Fruits by Xinhan Luo, Yujia Cui, Xiwen Yang, Guangfa Hu, Zhili Wu

“…Experimental studies were conducted to optimize the key parameters of the custom-built laser scoring machine, aiming to improve scoring qualification rates. …”
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Improving SVM performance through data reduction and misclassification analysis with linear programming by Carlos Aníbal Suárez, Mauricio Castro, Mariuxi Leon, Carlos Martin-Barreiro, Michael Liut

“…Abstract In the dual optimization problem behind Support Vector Machine (SVM), each data point corresponds to a decision variable. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…The accuracy of the assessment of the transport stress state of meat sheep after the optimization of three parameters was 100%, 90.91%, and 93.33%, and the classification accuracy of the overall model reached 94.92%. …”
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Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau by Zi-han Chen, Hao-tian Wu, Zhou Yao, Qian Liu, Hong-mei Zhang, Xiao-chen Li, Li-qing Yao, Xue Yang

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Federated Learning for Human Activity Recognition: Overview, Advances, and Challenges by Ons Aouedi, Alessio Sacco, Latif U. Khan, Dinh C. Nguyen, Mohsen Guizani

“…Federated Learning (FL) is a promising paradigm for HAR that enables the collaborative training of machine learning models on decentralized devices while preserving data privacy. …”
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A Framework for Real-Time Autonomous Robotic Sorting and Segregation of Nuclear Waste: Modelling, Identification and Control of Dexter^TM Robot by Mithun Poozhiyil, Omer F. Argin, Mini Rai, Amir G. Esfahani, Marc Hanheide, Ryan King, Phil Saunderson, Mike Moulin-Ramsden, Wen Yang, Laura Palacio García, Iain Mackay, Abhishek Mishra, Sho Okamoto, Kelvin Yeung

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