Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets by Muhammad Khahfi Zuhanda, Lisya Permata, Hartono, Erianto Ongko, Desniarti

“…In this study, we also compared the application of ADASYN and SMOTE on the Naïve Bayes algorithm. The results show that ADASYN outperforms SMOTE across all key metrics—accuracy, precision, recall, and F1-Score—while the accuracy improvements were statistically significant (p-value = 0.00903).…”
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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…This method divides the agent’s surrounding space into discrete and continuous action spaces. The PSO algorithm performs a global search in the continuous space to obtain a continuous candidate solution, while DQN learns a policy in the discrete space to obtain a discrete candidate solution. …”
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A Modified TCP BBR to Enable High Fairness in High-Speed Wireless Networks by Jinlin Xu, Wansu Pan, Haibo Tan, Longle Cheng, Xiru Li, Xiaofeng Li

“…Simulations and real network experiments have shown that the BBR–PG algorithm retains the throughput advantages of the original BBR algorithm while significantly enhancing fairness. …”
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HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks by Luca Marchetti, Rosario Lombardo, Corrado Priami

“…HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA). HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. …”
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Data augmentation scheme for federated learning with non-IID data by Lingtao TANG, Di WANG, Shengyun LIU

“…To solve the problem that the model accuracy remains low when the data are not independent and identically distributed (non-IID) across different clients in federated learning, a privacy-preserving data augmentation scheme was proposed.Firstly, a data augmentation framework for federated learning scenarios was designed.All clients generated synthetic samples locally and shared them with each other, which eased the problem of client drift caused by the difference of clients’ data distributions.Secondly, based on generative adversarial network and differential privacy, a private sample generation algorithm was proposed.It helped clients to generate informative samples while preserving the privacy of clients’ local data.Finally, a differentially private label selection algorithm was proposed to ensure the labels of synthetic samples will not leak information.Simulation results demonstrate that under multiple non-IID data partition strategies, the proposed scheme can consistently improve the model accuracy and make the model converge faster.Compared with the benchmark approaches, the proposed scheme can achieve at least 25% accuracy improvement when each client has only one class of samples.…”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

“…Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of-the-art DE algorithm. …”
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On the issue of a new solution of the materials resistance contact problem on compression of elastic cylinders in contact with parallel generators by Т. Брим, Б. Абдеев, Г. Муслиманова, С. Байгереев, Г. Байзакова

“…Based on this model, it is possible to determine only the stresses in parallel contacting cylinders, while the calculation of displacements, in this case, is not possible. …”
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Integrating path planning and task scheduling in autonomous drone operations by Ahmed KAMIL, Basim MAHMOOD

“…  The efficiency and adaptability of drone operations depend heavily on two critical components: path planning and task scheduling. While the literature provides extensive research on these algorithms independently, there is a severe lack of studies addressing their combined impact on drone performance. …”
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MAB-RSP: Data pricing based on Stackelberg game in MCS by Yongjiao Sun, Xueyan Ma, Anrui Han

“…Experiments demonstrate that the algorithm improves revenue while ensuring balanced benefits for all participants.…”
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Efficient Reasoning upon Fusion of Many Data Sources by Chase Alexander Yakaboski, Eugene Santos

“…This extension quickly yields a reasoning bottleneck that we overcome by leveraging a representation modification algorithm.  With this algorithm, we show how reasoning complexity upon fusion of many sources can be significantly reduced while maintaining the underlying probability semantics of all sources. …”
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Research on secure transport strategy of mobile edge computing based on deep reinforcement learning by WANG Yijun, LI Jiaxin, YAN Zhiying, LYU Jingying, QIAN Zhihong

“…Firstly, the mobile edge computing system based on unmanned aerial vehicle (UAV) was studied, which was composed of<italic> I</italic> user devices, <italic>M</italic> legal UAV (L-UAV) and <italic>N</italic> eavesdropping UAV (E-UAV). Secondly, while ensuring the unloading of L-UAV within a specified period, the multi-agent depth deterministic policy gradient (Attention-MADDPG) algorithm with the addition of attention mechanism was adopted to solve and optimize the problem with the aim of maximizing the safety unloading efficiency of the communication system. …”
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A space-time least-squares support vector regression scheme for inverse source problem of the time-fractional wave equation by A. Mohammadi, A. Tari Marzabad

“…In this work, we present a novel numerical approach for addressing the fractional inverse source problem by a machine learning algorithm and considering the ideas behind the spectral methods. …”
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Research on Mode Shift Control of Multimode Hybrid Systems Based on Hybrid Model Prediction by Xinxin Zhao, Jiadian Liu, Bing Li

“…However, the simulation time of the HMPC algorithm is about 27% less than that of the MPC algorithm. …”
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Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents by Lida Barba, Nibaldo Rodríguez, Cecilia Montt

“…The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. …”
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Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment by Jing Zhang, Jingjing Liu, Zhong Wan

“…Then, an interactive algorithm is developed to find a compromising solution of the uncertain model. …”
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Research on Runway Blockage Probability through Simulation by Wan-Li Wei, Ye-Qing Chen, Zhen-Qing Wang, Jian-Hui Wang, Xin-Jian Ren, Shang Ma

“…On the basis of Mathematica, a simulation is performed by judging whether the inequality group has a solution domain. An improved algorithm for judging whether an airport has a minimum takeoff and landing window is proposed. …”
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Redefining the high variable genes by optimized LOESS regression with positive ratio by Yue Xie, Zehua Jing, Hailin Pan, Xun Xu, Qi Fang

“…Results We developed a robust feature selection algorithm that leverages optimized locally estimated scatterplot smoothing regression (LOESS) to precisely capture the relationship between gene average expression level and positive ratio while minimizing overfitting. …”
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Optimal Scheduling of Multi-energy System Considering Economy and Energy Conservation by Chenxi Wu, Hanxiao Hong, Suoyin Ni, Y. L. Lou

“…Simulated annealing algorithm (SAA) is employed to energy-saving scheduling of the system with “exergy assessment” method. …”
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Position Selection and Collision-Free Path Planning for Fruit Picking Robots by Yonghee Cho, Dongwoon Choi, Kwangeun Ko, Jong Hyeon Park

“…Additionally, a method for collision-free path planning in joint space using the model predictive artificial potential field (MPAPF) algorithm is proposed. The effectiveness of the proposed position selection and path planning algorithms was validated through harvesting simulations and a collision-free path was validated in experiments.…”
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МЕСHANICAL BEHA VIOR OF GRADED HONEYCOMB AND ITS MULTI-OBJECTIVE OPTIMAL DESIGN by CHEN BiMin, HUANG XiaoDi

“…That the graded honeycomb recommended by the NSGA-I algorithm is compared with the homogeneous honeycomb. …”
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