A fast physics-based perturbation generator of machine learning weather model for efficient ensemble forecasts of tropical cyclone track by Jingchen Pu, Mu Mu, Jie Feng, Xiaohui Zhong, Hao Li

“…Although emerging artificial intelligence (AI)-based weather models offer high forecast accuracy and improved computational efficiency, they still face considerable challenges in ensemble forecasting applications, due to the unclear error growth dynamic and the lack of suitable ensemble methods in AI-based models. …”
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An Automatic Damage Detection Method Based on Adaptive Theory-Assisted Reinforcement Learning by Chengwen Zhang, Qing Chun, Yijie Lin

“…Current damage detection methods based on model updating and sensitivity Jacobian matrixes show a low convergence ratio and computational efficiency for online calculations. …”
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Mathematical Methods Applied to the Problem of Dairy Cow Replacements: A Scoping Review by Osvaldo Palma, Lluis M. Plà-Aragonés, Alejandro Mac Cawley, Víctor M. Albornoz

“…This research underscores the importance of these methods in improving the efficiency, profitability, and sustainability of dairy farming operations. …”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

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An Optimized Path Planning Method for Coastal Ships Based on Improved DDPG and DP by Yiquan Du, Xiuguo Zhang, Zhiying Cao, Shaobo Wang, Jiacheng Liang, Fengge Zhang, Jiawei Tang

“…In this paper, an optimized path planning method for coastal ships based on improved Deep Deterministic Policy Gradient (DDPG) and Douglas–Peucker (DP) algorithm is proposed. …”
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Efficient IP address retrieval using a novel octet based encoding technique for high speed lookup to improve network performance by Veeramani Sonai, Indira Bharathi, Sajjad Shaukat Jamal, Zaid Bassfar, Sameer Abdullah Nooh

“…This paper proposes an efficient deterministic approach to encoding IP prefixes that reduces storage complexity. …”
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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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Thermo‐Electro‐Mechanical Modeling of Failure: Application to Long‐Term Reliability of Aging Transmission Lines by Eduardo A. Barros De Moraes, K. C. Prakash, Mohsen Zayernouri

“…We study four representative scenarios deterministically and propose the Probabilistic Collocation Method (PCM) as a tool to understand the stochastic behavior of the system. …”
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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. …”

Hybridization of stochastic hydrological models and machine learning methods for improving rainfall-runoff modeling by Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick K. Ronoh, Stephen E. Moore

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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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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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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. …”

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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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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