Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…The feasibility and effectiveness of the algorithm is verified by comparing the baseline algorithm.…”
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An Automatic Generalization Method of a Block-Based Digital Depth Model Based on Surface Curvature Features by Dong Wang, Jian Dong, Lulu Tang, Mengkai Ma, Tian Xie

“…Furthermore, this paper designs validity and comparative experiments to analyze the proposed algorithm through experimental analysis. The results demonstrate that the algorithm can be applied to the multi-scale construction of DDM seabed terrain, while maintaining the integrity of both flat and complex seabed landforms, and significantly enhancing the computational efficiency of the DDM automatic generalization process.…”
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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

“…Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp Swarm Algorithm (LF-SSA), Mixed-Integer Linear Programming (MILP) and tools like HOMER Pro 3.12–3.16 and MATLAB 9.1–9.13, which have been instrumental in optimizing HRESs. …”
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Research on Fault Diagnosis Method of High-Speed EMU Air Compressor Based on ICEEMDAN and Wavelet Threshold Combined Noise Reduction by Liqiang Peng, Akang Guo, Shuzhao Zhang

“…This approach ensures denoising while preserving the integrity of the original signal. …”
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Analysis and Prediction of Grouting Reinforcement Performance of Broken Rock Considering Joint Morphology Characteristics by Guanglin Liang, Linchong Huang, Chengyong Cao

“…Notably, the Random Forest (RF) algorithm excels in rapid and accurate predictions when handling similar training data, while the ANN-based MCD algorithm consistently delivers stable and precise results across diverse datasets.…”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Optimizing Sampling Points and Path Planning for Soil Monitoring in Agricultural Land by Jing Wang, Zhiqiang Zhai, Guangdong Xu, Ruoyu Zhang, Xin Zhang, Rong Hu

“…Furthermore, the threshold-based hybrid algorithm consistently yields optimal or near-optimal paths while reducing the path planning time, with an average duration of 1.0783 s for path planning. …”
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Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization by Zhenqing Wu, Wenwu Gong, Ziying Yu, Liuxin Zhu, Lili Yang

“…Abstract We propose the replica exchange adaptively weighted stochastic gradient Langevin dynamics (REAWSGLD) algorithm, designed explicitly for Bayesian learning with complex energy landscapes encountered in big data problems. …”
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Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks by Israel Edem Agbehadji, Samuel Ofori Frimpong, Richard C Millham, Simon James Fong, Jason J Jung

“…During the simulation, the dynamic nature of the proposed DEEC-KSA was observed using different parameters, which were expressed in percentages as 0.1%, 4.5%, 11.3%, and 34% while the percentage of the parameter for comparative algorithms was 10%. …”
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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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