Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game by Hongxu Zhu, Shufan Wu

“…Furthermore, a novel policy iteration (PI) algorithm for solving this equilibrium based on fixed-point iteration is proposed. …”
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A non‐convex ternary variational decomposition and its application for image denoising by Liming Tang, Liang Wu, Zhuang Fang, Chunyan Li

“…In image denoising application, the proposed model can successfully remove noise while effectively preserving image edges and constructing textures. An alternating direction iteration algorithm combining with iteratively reweighted l1 algorithm, projection algorithm and wavelet soft threshold algorithm is introduced to effectively solve the proposed model. …”
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Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…Numerical results also show that the parallel solver called comeSn_JFNK can achieve an acceleration of over 10 times for KAIST-3A benchmark problems and approximately 30 times for C5G7-TD2 cases compared to the original parallel comeSn code using the traditional source iteration/power iteration methods. These solutions indicate that the JFNK methods offer significant acceleration for solving both steady-state and transient SN neutron transport models compared to traditional source iteration/power iteration methods. …”

Maximum Penalized-Likelihood Structured Covariance Estimation for Imaging Extended Objects, with Application to Radio Astronomy by Aaron Lanterman

“…We also investigate algorithm variations that perform a generic smoothing step at each iteration. …”
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Computationally expensive constrained problems via surrogate-assisted dynamic population evolutionary optimization by Zan Yang, Chen Jiang, Jiansheng Liu

“…Abstract This paper proposes a surrogate-assisted dynamic population optimization algorithm (SDPOA) for the purpose of solving computationally expensive constrained optimization problems, in which the population is dynamically updated based on the real-time iteration information to achieve targeted searches for solutions with different qualities. …”
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Privacy-preserving ADP for secure tracking control of AVRs against unreliable communication by Kun Zhang, Kezhen Han, Zhijian Hu, Guoqiang Tan

“…To mitigate information leakage and unauthorized access in vehicular network systems, an encrypted guaranteed-cost policy iteration algorithm is developed, incorporating encryption and decryption schemes between the vehicle and the cloud based on the tracking dynamics. …”
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Gradient Method with Step Adaptation by Vladimir Krutikov, Elena Tovbis, Svetlana Gutova, Ivan Rozhnov, Lev Kazakovtsev

“…The paper solves the problem of constructing step adjustment algorithms for a gradient method based on the principle of the steepest descent. …”
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Use of the multigrid methods for heat radiation problem by Naji A. Qatanani

“…To demonstrate the high efficiency of these iterations, we construct some numerical experiments for different enclosure geometries.…”
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. …”
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An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection by Mengxin Lu, Shujuan Wang

“…The random generation and the nearest neighbor algorithms are employed to construct the initial solution, followed by roulette selection, elite selection, and a best individual retention strategy to refine the population for the next iteration. …”
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A Semiblind Receiver for a Two-Way UAV-Aided PIC System Based on the PARAFAC Model by Xi Han, Yichen Liu, Qin Liu, Lijun Wang, Zhengping Li

“…This system eliminates impulse interference through an adaptive filter based on the least mean square (LMS) and uses the received signal transmitted by the UAVs to construct a parallel factor (PARAFAC) model. Based on the identifiability condition of the PARAFAC model, a pulse interference cancellation orthogonal pilot tensor (PIC-OPT) receiver without iteration is proposed. …”
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RIS-assisted terahertz frequency band vehicle network capacity optimization by Fatang CHEN, Xiaoling LIU, Dan WANG, Ruofan ZHANG

“…In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downlink vehicle network.Considering the constraints of limited total system power, QoS constraints of cellular mobile users, and randomness constraints of vehicle and user locations, a hybrid optimization model was established for optimal power allocation and optimal deployment of RIS with the aim of maximizing the total rate of vehicle users.Based on the balance method, linear transformation method, and element elimination method, the original NP-hard problem was transformed into a convex optimization problem with complex correlation constraints and multivariate coupling.The inner layer iteration was based on the Lagrange multiplier method to solve the optimal power allocation, and the outer layer iteratively solved the optimal deployment of RIS based on a improved genetic algorithm.The simulation results show that rationally deploying the number and distribution density of RIS nodes based on optimal power allocation can save costs while achieving a higher target total capacity.…”
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Initial position detection scheme based on discrete pulse signal injection for PMSM by Weiping Duan, Chen Cen, Chen Zhang

“…The entire scheme adopts a discrete approach, ensuring a holistic and less complex algorithm. Moreover, a novel iteration method based on interpolation is introduced, leveraging the reconstructed cost function to achieve rapid convergence and minimize the number of injected pulses. …”
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3D Reconstruction and Deformation Detection of Rescue Shaft Based on RGB-D Camera by Hairong Gu, Bokai Liu, Lishun Sun, Mostak Ahamed, Jia Luo

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Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology by Ning Xu, Qingshan Meng, Fengping Liu, Zhihe Li, Guangming Wang, Na Guo, Wenxuan Wu

“…In the loop frame matching, an optimization algorithm combining normal distribution transformation and iterative nearest point is used to reduce the cumulative error significantly. …”
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Multi-Level Asynchronous Robust State Estimation for Distribution Networks Considering Communication Delays by Xianglong Zhang, Ying Liu, Songlin Gu, Yuzhou Tian, Yifan Gao

“…Then, an event-driven broadcast transmission strategy is designed to unify boundary information exchanged between levels during iteration. A multi-threaded parallel framework is constructed to decouple receiving, computation, and transmission tasks, thereby enhancing asynchronous scheduling capabilities across threads. …”
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Node selection method in federated learning based on deep reinforcement learning by Wenchen HE, Shaoyong GUO, Xuesong QIU, Liandong CHEN, Suxiang ZHANG

“…To cope with the impact of different device computing capabilities and non-independent uniformly distributed data on federated learning performance, and to efficiently schedule terminal devices to complete model aggregation, a method of node selection based on deep reinforcement learning was proposed.It considered training quality and efficiency of heterogeneous terminal devices, and filtrate malicious nodes to guarantee higher model accuracy and shorter training delay of federated learning.Firstly, according to characteristics of model distributed training in federated learning, a node selection system model based on deep reinforcement learning was constructed.Secondly, considering such factors as device training delay, model transmission delay and accuracy, an optimization model of accuracy for node selection was proposed.Finally, the problem model was constructed as a Markov decision process and a node selection algorithm based on distributed proximal strategy optimization was designed to obtain a reasonable set of devices before each training iteration to complete model aggregation.Simulation results demonstrate that the proposed method significantly improves the accuracy and training speed of federated learning, and its convergence and robustness are also well.…”
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Node selection method in federated learning based on deep reinforcement learning by Wenchen HE, Shaoyong GUO, Xuesong QIU, Liandong CHEN, Suxiang ZHANG

“…To cope with the impact of different device computing capabilities and non-independent uniformly distributed data on federated learning performance, and to efficiently schedule terminal devices to complete model aggregation, a method of node selection based on deep reinforcement learning was proposed.It considered training quality and efficiency of heterogeneous terminal devices, and filtrate malicious nodes to guarantee higher model accuracy and shorter training delay of federated learning.Firstly, according to characteristics of model distributed training in federated learning, a node selection system model based on deep reinforcement learning was constructed.Secondly, considering such factors as device training delay, model transmission delay and accuracy, an optimization model of accuracy for node selection was proposed.Finally, the problem model was constructed as a Markov decision process and a node selection algorithm based on distributed proximal strategy optimization was designed to obtain a reasonable set of devices before each training iteration to complete model aggregation.Simulation results demonstrate that the proposed method significantly improves the accuracy and training speed of federated learning, and its convergence and robustness are also well.…”
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Research on High-Precision Motion Planning of Large Multi-Arm Rock Drilling Robot Based on Multi-Strategy Sampling Rapidly Exploring Random Tree* by Qiaoyu Xu, Yansong Lin

“…A multi-strategy sampling mechanism is constructed by integrating DRL position sphere sampling, spatial random sampling, and goal-oriented sampling. …”
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Research on low-Impact development layouts in old urban residential communities based on multi-objective optimization. by Fuqin Liu, Yijun Fan, Xinran Liu, Yanjuan Li

“…This research focuses on an old residential community in Beijing utilizing the SWMM in combination with the NSGA-II algorithm. A Pareto optimal curve was identified iteratively, with construction costs, runoff reduction effects, and node overload time as the optimization objectives and the maximum area for the low impact development (LID) layout as a constraint. …”
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