A machine learning model for early detection of sexually transmitted infections by Juma Shija, Judith Leo, Elizabeth Mkoba

“…The dataset was split into a 70%:15%:15% ratio for training, testing, and validation, respectively, and five machine learning algorithms were evaluated: AdaBoost, Support Vector Machine, Random Forest, Decision Tree, and Stochastic Gradient Descent. …”
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Integrating Artificial Intelligence and Computational Algorithms to Optimize the 15-Minute City Model by Marwa Abouhassan, Samah Elkhateeb, Raneem Anwar

“…We reveal how AI-driven algorithms, machine learning techniques, and advanced data analytics can enhance urban planning, improve accessibility, and foster social integration. …”
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Unified ELM suppression on KSTAR and DIII-D via adaptive feedback control strategies by R. Shousha, S.K. Kim, K.G. Erickson, S.H. Hahn, A.O. Nelson, N.C. Logan, S.M. Yang, Q.M. Hu, R. Wilcox, J.-K. Park, C. Paz-Soldan, A. Battey, M.W. Kim, G. Shin, W.H. Ko, Y.M. Jeon, J.H. Lee, J. Jang, D.C. Seo, J. Abbate, A. Rothstein, E. Kolemen

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Optimizing Problem-Solving in Technical Education: An Adaptive Learning System Based on Artificial Intelligence by Rommel Gutierrez, William Eduardo Villegas-Ch, Alexandra Maldonado Navarro, Sergio Lujan-Mora

“…This study proposes an adaptive learning system powered by deep learning algorithms designed to optimize problem-solving skills in technical college students. …”
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Bearing Fault Diagnosis Based on Parameter Optimized VMD and ELM with Improved SSA by Yang Sen, Wang Hengdi, Cui Yongcun, Li Chang, Tang Yuanchao

“…Aiming at the problem that the initial fault signal of rolling bearings is weak and the fault characteristic is difficult to extract, this study proposes a rolling bearing fault diagnosis method based on variational modal decomposition (VMD) for adaptive parameter optimization based on the improved sparrow search algorithm (SSA) and the extreme learning machine (ELM) with multi-layer feature vector fusion. …”
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Rapid detection method for pork freshness using fusion spectroscopy and improved BAS-LSSVM by WANG Yao, REN Xiaozhen

“…By combining SG smoothing filtering and standard normal variables for data preprocessing, combining window competitive adaptive reweighted sampling and iterative continuous projection for feature selection, regularization parameters and kernel parameters of Least-Square Support Vector Machine were optimized by the Improved Beetle Antennae Search Algorithm, a fast non-destructive detection method for meat freshness (TVB-N) was completed. …”
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Semi-Supervised Attribute Selection Algorithms for Partially Labeled Multiset-Valued Data by Yuanzi He, Jiali He, Haotian Liu, Zhaowen Li

“…In machine learning, when the labeled portion of data needs to be processed, a semi-supervised learning algorithm is used. …”
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Crop Monitoring System Using IoT, Solar Energy and Decision Tree Algorithm by Ricardo Yauri, Luis Cuyubamba, Stefano Nuñez

“…This paper aims to design an Internet of Things-based monitoring system where the specific objectives are focused on building a solar-powered power stage and integrating machine learning algorithms to help determine crop health. …”
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VF-CART: A communication-efficient vertical federated framework for the CART algorithm by Yang Xu, Xuexian Hu, Jianghong Wei, Hongjian Yang, Kejia Li

“…There is an increasing trend in adapting machine learning algorithms to the VFL setting. …”
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Fault location and isolation technology for power grid automation based on intelligent algorithms by Qi Guo, Fuhe Wang, Suxia Cheng, Ke Wang, Yifan Zhang

“…Problem statement Conventional fault management methods, like rule-based and heuristic methods, have limitations in both accuracy and real-time adaptability. To address these issues, this study proposes and assesses two intelligent algorithms: the Fault Localization Algorithm (FLA) and the Fault Isolation Algorithm (FIA). …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…The accuracy and robustness of model recognition are improved by combining spectral, infrared, laser and other sensor data. The model adaptive adjustment algorithm should be developed to adjust strategies and parameters according to real-time feedback and adapt to different fruit picking operations and different picking environmental conditions. …”
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A Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction by Jordan J. Bird, Diego R. Faria, Luis J. Manso, Anikó Ekárt, Christopher D. Buckingham

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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…By comparing these algorithms, we can clarify the advantages and adaptability of different algorithms in different scenarios. …”
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FedCVG: a two-stage robust federated learning optimization algorithm by Runze Zhang, Yang Zhang, Yating Zhao, Bin Jia, Wenjuan Lian

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Trajectory Planning of Unmanned Aerial Vehicles in Complex Environments Based on Intelligent Algorithm by Zhekun Cheng, Jueying Yang, Jinfeng Sun, Liangyu Zhao

“…Thirdly, the research trend from 2010 to 2024, together with the implementation, advantages, and existing problems of machine learning, evolutionary algorithms, and swarm intelligence, are compared. …”
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Features extraction based on Naive Bayes algorithm and TF-IDF for news classification. by Li Zhang

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Scene Matching Method for Children’s Psychological Distress Based on Deep Learning Algorithm by Junli Su

“…Based on the summary and analysis of previous research works, this paper expounded the research status and significance of the scene matching method for children’s psychological distress, elaborated the development background, current status, and future challenges of deep learning algorithm, introduced the methods and principles of depth spatiotemporal feature extraction algorithm and dynamic scene understanding algorithm, constructed a scene matching model for children’s psychological distress based on deep learning algorithm, analyzed the scene feature extraction and matching function construction of children’s psychological distress, proposed a scene matching method for children’s psychological distress based on deep learning algorithm, performed scene feature matching and information processing of children’s psychological distress, and finally conduced a simulation experiment and analyzed its results. …”
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Control algorithm for an elastic-viscoplastic model to study processes of shock interaction of bodies by V. L. Lapshin, Е. V. Zenkov

“…In engineering practice, dynamic processes, with the help of which mechanics of interaction of machine components and structural elements are described and studied, are of great importance. …”
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Machine Learning in Sensory Analysis of Mead—A Case Study: Ensembles of Classifiers by Krzysztof Przybył, Daria Cicha-Wojciechowicz, Natalia Drabińska, Małgorzata Anna Majcher

“…In the next stage, experiments were carried out to classify the type of mead using algorithms such as Random Forest (RF), adaptive boosting (AdaBoost), Bootstrap aggregation (Bagging), K-Nearest Neighbors (KNN), and Decision Tree (DT). …”
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Probabilistic Entropy EMD Thresholding for Periodic Fault Signal Enhancement in Rotating Machine by Jian Dang, Rong Jia, Hua Wu, Xingqi Luo, Diyi Chen

“…Therefore, a probabilistic entropy EMD thresholding algorithm for periodic fault signal enhancement in rotating machine is proposed in this paper. …”
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