Evaluating the Stability of Numerical Schemes for Fluid Solvers in Game Technology by Craig R. Stark, Declan A. Diver

“…To exemplify the method to evaluate numerical stability, a range of finite difference schemes is considered. …”
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A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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An Innovative Inversion Method of Potato Canopy Chlorophyll Content Based on the AFFS Algorithm and the CDE-EHO-GBM Model by Xiaofei Yang, Qiao Li, Honghui Li, Hao Zhou, Jinyan Zhang, Xueliang Fu

“…Gradient Boosting Machine (GBM) model parameters were optimized using a hybrid strategy improved Elephant Herd Optimization (EHO) algorithm (CDE-EHO) that combines Differential Evolution (DE) and Cauchy Mutation (CM). …”
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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…This study explores how the synergy between DRL and EAs, including Genetic Algorithms (GAs) and Differential Evolution (DE), can enhance the efficiency and sustainability of smart city energy systems. …”
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APPROACH OF PROCESSING, CLASSIFICATION AND DETECTION OF NEW CLASSES AND ANOMALIES IN HETEROGENIOUS AND DIFFERENT STREAMS OF DATA by R. A. Bagutdinov

“…The level of false positives in the developed algorithm is rather low and can be considered insignificant. …”
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CLDP-pFedAvg: Safeguarding Client Data Privacy in Personalized Federated Averaging by Wenquan Shen, Shuhui Wu, Yuanhong Tao

“…Furthermore, we provide a convergence analysis of the clipping-enabled differentially private meta-based FedAvg algorithm. The proposed strategy is evaluated across various datasets, and the findings indicate that our approach offers improved privacy protection while maintaining model accuracy.…”
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An Adaptive Parameter Evolutionary Marine Predators Algorithm for Joint Resource Scheduling of Cooperative Jamming Networked Radar Systems by Dejiang Lu, Siyi Cheng, You Chen, Xi Zhang, Haoyang Li, Tianjian Yang

“…Considering the scene constraints, an Improved Adaptive Parameter Evolution Marine Predators Algorithm is designed as an optimizer and embedded in the proposed framework to jointly optimize the platform beam allocation and jamming mode selection. …”
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Applying Machine Learning Algorithms for Spatial Modeling of Flood Susceptibility Prediction over São Paulo Sub-Region by Temitope Seun Oluwadare, Marina Pannunzio Ribeiro, Dongmei Chen, Masoud Babadi Ataabadi, Saba Hosseini Tabesh, Abiodun Esau Daomi

“…This study employs four ML algorithms—differential evolution (DE), naïve Bayes (NB), random forest (RF), and support vector machines (SVMs)—to develop flood susceptibility models using 16 predictor variables. …”
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Research for the Positioning Optimization for Portable Field Terrain Mapping Equipment Based on the Adaptive Unscented Kalman Filter Algorithm by Jiaxing Xie, Zhenbang Yu, Gaotian Liang, Xianbing Fu, Peng Gao, Huili Yin, Daozong Sun, Weixing Wang, Yueju Xue, Jiyuan Shen, Jun Li

“…Data fusion is carried out using the Unscented Kalman Filter (UKF) algorithm. Building on this, this study combines the good point set and Opposition-based Differential Evolution for a joint improvement of the Slime Mould Algorithm. …”
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Evaluating the Performance of SVM, Isolation Forest, and DBSCAN for Anomaly Detection by Lu Haowen

“…This study evaluates the suitability of three algorithms—Support Vector Machine (SVM), Isolation Forest, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) by comparing their accuracy and time efficiency in detecting outliers in different types of datasets. …”
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A modified TOPSIS algorithm for the assessment of sports quality in higher education using circular pythagorean fuzzy information by Jiapeng Li, Yitong Zhang

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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…This paper empirically uses data from rural banks in 30 provinces in China to classify the different characteristics of rural banks’ performance in order to better evaluate their performance.…”
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Evolutionary Artificial Intelligence Algorithm for Optimizing Step Phase Detection Based on Foot-Mounted Triaxial Accelerometer Data by P. A. Khmarskiy

“…The aim of this study was to develop and experimentally validate an algorithm for automatic selection of filter frequency characteristics and detection threshold in order to enhance the accuracy and reliability of gait phase detection. …”
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RESULTS OF INTRODUCTING THE PRINCIPLES OF INFECTION CONTROL INTO THE PRACTICE OF THE BELARUS REPUBLICAN TUBERCULOSIS SERVICE by G. L. Gurevich, A. P. Astrovko, E. M. Skryagina, D. A. Klimuk, O. M. Kalechits, A. E. Skryagin

“…The health protection in healthcare workers and patients in different healthcare organizations may be compared on the basis of qualitative and quantitative evaluation of the efficiency of tuberculosis IC measures. …”
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On modeling random data to evaluate the performance of statistical tests in cryptography by U. Y. Palukha, M. A. Prokharchyk, Yu. S. Kharin

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A Power Control Algorithm for V2V Communication Networks Based on Dynamic Multi-Objective Optimization by Mengyu Ma, Zihao Gu, Chao Wang, Zuxing Li, Jianyao Hu, Fuqiang Liu

“…We propose a prediction-based dynamic multi-objective optimization evolutionary algorithm (DMOEA) that facilitates the evolution of the solution population by predicting the centroid of the power allocation decision set in a new environment, so that transmission decisions can be made to adapt to the highly dynamic environment. …”
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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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Identification of Biomarkers Associated with Heart Failure Caused by Idiopathic Dilated Cardiomyopathy Using WGCNA and Machine Learning Algorithms by Mengyi Sun, Linping Li

“…Candidate genes were identified by intersecting the key module genes identified via WGCNA with DEGs and further screened via the support vector machine-recursive feature elimination (SVM-RFE) method and the least absolute shrinkage and selection operator (LASSO) algorithm. At last, the biomarkers were validated and evaluated the diagnostic efficacy by the area under curve (AUC) value and further confirmed the differential expression in the IDCM-HF and NF groups using an external database. …”
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Integrated Machine Learning Algorithms-Enhanced Predication for Cervical Cancer from Mass Spectrometry-Based Proteomics Data by Da Zhang, Lihong Zhao, Bo Guo, Aihong Guo, Jiangbo Ding, Dongdong Tong, Bingju Wang, Zhangjian Zhou

“…By processing and normalizing serum polypeptide differential peaks from 240 patients, we employed eight distinct ML algorithms to classify and analyze these differential polypeptide peaks, subsequently constructing receiver operating characteristic (ROC) curves and confusion matrices. …”
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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

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