Advances in UAV Path Planning: A Comprehensive Review of Methods, Challenges, and Future Directions by Wenlong Meng, Xuegang Zhang, Lvzhuoyu Zhou, Hangyu Guo, Xin Hu

“…This article presents an extensive overview of methodologies for UAV route planning, including deterministic models, stochastic sampling techniques, biologically inspired methods, and integrated algorithmic frameworks. …”
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Uncertainty modeling of excavator’s variable displacement pump based on EFAST and MH-Cuckoo method by Su Deying, Lian Xiaozhen, Xie Meina

“…The results demonstrate that EFAST and MHCuckoo methods can reliably and efficiently perform uncertainty analysis. …”
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Research on Parallel Computing Method for Neutron Transport on Tetrahedral Unstructured Meshes Based on COME by ZHONG Yangyu, ZHANG Tiancheng, ZHOU Xiafeng

“…Owing to the inhomogeneous distribution of materials in complex geometric reactor cores, traditional source iteration methods face significant challenges in solving neutron transport equations efficiently. …”

Electromagnetic Scattering of Electrically Large Ship above Sea Surface with SBR-SDFM Method by Lixin Guo, Tiantian Feng

“…Accuracy and performance of this method are validated and evaluated by comparing with multilevel fast multipole method of FEKO for electrically small objects. …”
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A Novel Method Based on Particle Flow Filters for Stellar Gyroscope Parameter Estimations by Erol Duymaz

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Development of Hybrid Neutron Dynamics Algorithm Based on Transient Fission Matrix Combined Method by LI Yuehang, HE Donghao, LIU Xiaojing, PAN Qingquan

“…The deterministic method and the Monte Carlo method are used in the transient analysis of nuclear reaction systems, but high-fidelity methods are inefficient in computation, and the accuracy of the low order method is not sufficient. …”

Optimization Problem for Probabilistic Time Intervals of Quasi-Deterministic Output and Self-Similar Input Data Packet Flow in Telecommunication Networks by G. I. Linets, R. A. Voronkin, G. V. Slyusarev, S. V. Govorova

“…When managing traffic at the packet level in modern telecommunication networks, it is proposed to use methods that transform a self-similar stochastic packet flow into a quasi-deterministic one. …”
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Parameter uncertainties for imperfect surrogate models in the low-noise regime by Thomas D Swinburne, Danny Perez

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A Tactical Conflict Detection and Resolution Method for En Route Conflicts in Trajectory-Based Operations by Dong Sui, Kai Zhang

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Decision-Making Policy for Autonomous Vehicles on Highways Using Deep Reinforcement Learning (DRL) Method by Ali Rizehvandi, Shahram Azadi, Arno Eichberger

“…Automated driving (AD) is a new technology that aims to mitigate traffic accidents and enhance driving efficiency. This study presents a deep reinforcement learning (DRL) method for autonomous vehicles that can safely and efficiently handle highway overtaking scenarios. …”
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Quantitative operation risk assessment method for power grid with large-scale distributed new energy by Shuai ZHAO, Xiaolin ZHENG, Tao LU, Xiaojing YANG, Ning JIANG, Haipeng LIU

“…Finally, the application case results of actual power grid show that the risk assessment method proposed in this paper not only improves the risk assessment accuracy and calculation efficiency of the power grid with distributed new energy, but also can more comprehensively reflect the real-time operation risk characteristics of the system.…”
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FedDDPG: A reinforcement learning method for federated learning-based vehicle trajectory prediction by Jinlong Li, Ruonan Li, Guojie Ma, Weihong Yang, Hongye Wang, Zhaoquan Gu

“…However, trajectory data collected from roadside units often contains varying levels of noise, which poses unique challenges for traditional FL methods. To address these challenges, this paper proposes a personalized optimization solution called FedDDPG (Federated Learning with Deep Deterministic Policy Gradient) for VTP with FL paradigm. …”
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A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set by Haocheng DU, Shilong LI, Yuntao JU, Jinqi ZHANG

“…It transformed the model into a mixed-integer second-order conic planning problem by deterministically transforming the worst-case expectation and chance constraints in the objective function by using a dual transformation method. …”
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Pharmacoeconomic study of fluorescent lymphography and radionuclide diagnostics methods for sentinel lymph node detection in breast cancer by E. P. Kulikov, M. V. Shomova, D. S. Titov, A. N. Demko, M. A. Maistrenko

“…Sentinel lymph node (SLN) biopsy is a reliable diagnostic method used to assess the spread of the malignant process in regional lymph nodes. …”
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A new APSO-SPC method for parameter identification problem with uncertainty caused by random measurement errors by Peng Zhong, Xuanlong Wu, Li Zhu, Aohao Yang

“…In parameter identification problem, errors are common in measurement data, resulting in uncertainty in the identified parameters. Traditional deterministic methods cannot address this uncertainty. …”
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Optimization Research on Energy Management Strategies and Powertrain Parameters for Plug-In Hybrid Electric Buses by Lufeng Wang, Juanying Zhou, Jianyou Zhao

“…Subsequent to this, a combined multi-layer powertrain optimization method based on Genetic Algorithm-Optimal Adaptive Control of Motor Efficiency-Particle Swarm Optimization (GOP) is proposed. …”
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Abstract In highly dynamic vehicular networking scenarios, when Vehicle-to-Infrastructure links and Vehicle-to-Vehicle links share spectrum resources, the traditional distributed resource allocation method lacks global optimization and fails to respond to environmental changes in a timely manner, which leads to low spectral efficiency of the system. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

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A data-physical fusion method for economic dispatch considering high renewable penetration and security constraints by Yuchen Dai, Wei Xu, Xiaokang Wu, Minghui Yan, Feng Xue, Jianfeng Zhao

“…Conventional model-based methods of economic dispatch encounter significant challenges due to the increasing uncertainties brought about by high renewable penetration. …”
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Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. In this paper, we construct a reinforcement agent for intra-day dispatch to optimize generator output, using a twin delayed deep deterministic policy gradient algorithm based on pre-training and expert knowledge (PEK-TD3). …”
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