HGCS—A Multiplex Transmission Method for Wide-Area Unmanned Aerial Vehicle Cluster Inspection Data in Hybrid Networked Transmission Lines by Ruchao Liao, Xionggang Li, Jinchao Guo, Wenxing Sun, Guoqiang Li

“…To address these challenges, an effective optimization algorithm is required to balance the algorithmic performance while considering the fairness and QoS parameters. …”
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Quantum natural stochastic pairwise coordinate descent by Mohammad Aamir Sohail, Mohsen Heidari, S. Sandeep Pradhan

“…We develop a quantum optimization algorithm that leverages the geometry of the state space via this estimator while avoiding full-state tomography, as in conventional techniques. …”
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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

“…To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. …”
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The Role of Misclassification and Carbon Tax Policies in Determining Payment Time and Replenishment Strategies for Imperfect Product Shipments by Chun-Tao Chang, Yao-Ting Tseng

“…Theoretical analysis showed that profit exhibited joint concavity with respect to both payment time and replenishment time. An algorithm was also formulated to derive optimal solutions. …”
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Resource Allocation Schemes for Multiple Targets Tracking in Distributed MIMO Radar Systems by Xiyu Song, Nae Zheng, Ting Bai

“…Simulation results indicate that the proposed MFMLS and MFMLS_OAT algorithm outperform the existing algorithms. Moreover, the MFMLS algorithm can distinguish targets with different priorities, while the MFMLS_OAT algorithm can perform the tracking tasks with higher accuracy.…”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…This paper explores the integration of distributed photovoltaic (PV) systems and energy storage solutions to optimize energy management in 5G base stations. By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“…The results suggest that BERT embeddings combined with UMAP dimension reduction to no less than 15 dimensions provides a good basis for clustering, regardless of the specific clustering algorithm used. Moreover, while UMAP performed better than PCA in our experiments, tuning the UMAP settings showed little impact on the overall performance. …”
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Adaptive rumor propagation and activity contagion in higher-order networks by Yafang Dong, Liang’an Huo, Matjaž Perc, Stefano Boccaletti

“…We also apply a sequential quadratic programming algorithm to optimize the parameters of our model and validate its accuracy and applicability on real-world data. …”
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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. …”
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Computing mutual similarity of 3D human faces in nearly linear time. by Radek Ošlejšek, Petra Urbanová, Jiří Sochor

“…Our solution utilizes properties of facial scan geometry to optimize individual steps. Moreover, the algorithm deals with possible holes and other artifacts in polygonal meshes automatically. …”
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A comparison of tools used for tuberculosis diagnosis in resource-limited settings: a case study at Mubende referral hospital, Uganda. by Adrian Muwonge, Sydney Malama, Barend M de C Bronsvoort, Demelash Biffa, Willy Ssengooba, Eystein Skjerve

“…Clinical variables from a questionnaire and DZM were used to predict TB status in multivariable logistic and Cox proportional hazard models, while optimization and visualization was done with receiver operating characteristics curve and algorithm-charts in Stata, R and Lucid-Charts respectively.…”
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Fractional-Order Adaptive P-Laplace Equation-Based Art Image Edge Detection by Ming Chen

“…The experimental results demonstrate that the algorithm can remove the noise while preserving the texture and details of the image. …”
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Load-Balanced Dynamic SFC Migration Based on Resource Demand Prediction by Tian Sun, Hefei Hu, Sirui Zhang

“…Therefore, we propose the Resource Predictive Load Balancing SFC Migration (RP-LBM) algorithm in this paper. The algorithm uses CNN-AT-LSTM to predict VNF resource demands in advance, eliminating the delays associated with dynamic migrations and determining the optimal migration timing. …”
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Predicting the Attraction and Retention of Customers in Sports Pools in Isfahan City Using a Decision Tree: Presenting a Data Mining-Based Model by Seyed Masoud Mirsaeidi, Davood Nasr Esfahani

“…To evaluate the features, two algorithms—Grasshopper Optimization Algorithm (GOA) and Simulated Annealing (SA)—were used for feature selection, while classification algorithms, specifically Decision Tree (DT) and K-Nearest Neighbors (KNN), were employed to classify and recognize customer behavior. …”
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QoS Aware Service Scheduling Scheme for VANETs by Ajay Guleria, Kuldip Singh, Narottam Chand

“…They provide the requests to road side unit (RSU) while travelling. The job of RSU is to handle various requests in such a way so that the service ratio and the quality of service (QoS) is optimized. …”
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A cartographic generalization method for 3D visualization of trajectories in space–time cubes: case study of epidemic spread by Fei Yang, Jie Shen, Fengzhen Zhu, Junrui Zhang

“…The proposed method incorporates a 3D generalization algorithm that mitigates visual stickiness, while leveraging a 3D line field visualization technique to optimize opacity, thereby minimizing visual occlusion and spatial clutter. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…Our proposed RL-based algorithm leverages the actor-critic policy gradient method to learn optimal channel selection strategies by dynamically adapting to the environment and minimizing TTR. …”
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