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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High-Order Spectral Method of Density Estimation for Stochastic Differential Equation Driven by Multivariate Gaussian Random Variables by Hongling Xie

“…There are some previous works on designing efficient and high-order numerical methods of density estimation for stochastic partial differential equation (SPDE) driven by multivariate Gaussian random variables. …”
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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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A Practical Cache Partitioning Method for Multi-Core Processor on a Commercial Safety-Critical Partitioned RTOS by Taeho Kim

“…Validation in a flight simulation environment confirmed the practicality of the method in real-world scenarios.…”
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Age of Information Minimization in Vehicular Edge Computing Networks: A Mask-Assisted Hybrid PPO-Based Method by Xiaoli Qin, Zhifei Zhang, Chanyuan Meng, Rui Dong, Ke Xiong, Pingyi Fan

“…Simulation results show that the proposed MHPPO method achieves an approximately 28.9% reduction in AoI compared with the HPPO method and about a 23% reduction compared with the mask-assisted deep deterministic policy gradient (MDDPG).…”
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Reinforcement learning in electric vehicle energy management: a comprehensive open-access review of methods, challenges, and future innovations by Georginio Ananganó-Alvarado, Ignacio Umaña-Morel, Brian Keith-Norambuena

“…This review presents a structured synthesis of open-access research published between 2016 and 2024 on the application of reinforcement learning methods to electric vehicle energy optimization. The study formulates four guiding research questions to analyze types of learning algorithms, evaluation criteria, system-level constraints, and practical implementation aspects. …”
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Comparative Analysis of Some Methods and Algorithms for Traffic Optimization in Urban Environments Based on Maximum Flow and Deep Reinforcement Learning by Silvia Baeva, Nikolay Hinov, Plamen Nakov

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Double Critics and Double Actors Deep Deterministic Policy Gradient for Mobile Robot Navigation Using Adaptive Parameter Space Noise and Parallel Experience Replay by Wenjie Hu, Ye Zhou, Hann Woei Ho, Chun Zhang

“…This opens up new possibilities for improving the efficiency and effectiveness of other DRL methods.…”
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Distributionally Robust Policy and Lyapunov-Certificate Learning by Kehan Long, Jorge Cortes, Nikolay Atanasov

“…This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. …”
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Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

“…ObjectiveIn the new power system, energy storage devices are constrained by geographical limitations and single dispatch methods, leading to low utilization efficiency, which severely restricts the effective integration of renewable energy. …”
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A Comparative Study Between Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) Algorithms for Solar PV MPPT Control Under Partial Shading Conditions by Sampson E. Nwachukwu, Komla A. Folly, Kehinde O. Awodele

“…Simulation results show that SAC and DDPG algorithms outperform the P&O method under PSCs and varying irradiance levels. It is shown that the SAC algorithm exhibits superior performance, achieving high tracking efficiency and eliminating power oscillations near the PV MPP and GMPP compared to the DDPG method.…”
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Accelerated Computation of Linear Complementarity Problem in Dexterous Robotic Grasping via Newton-Subgradient Non-Smooth Multi-Step Greedy Kaczmarz Method by Zhiwei Ai, Chenliang Li

“…The methodology effectively mitigates inherent limitations of conventional randomized row selection, including unpredictable iteration counts and computational overhead from repeated Jacobian updates, while maintaining deterministic convergence behavior. The method’s convergence theory is rigorously established, with benchmark analyses demonstrating marked improvements in computational efficiency over the NSNGRK framework. …”
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An Improved Parameter Extraction Optimization Algorithm for RF Devices by Shengsen Yang, Zihan Xu, Kun Ren

“…Experimental results show that, compared to traditional optimization algorithms, the proposed method significantly improves curve fitting accuracy, computational efficiency, and stability, highlighting its application value in RF device parameter extraction.…”
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Existence, uniqueness, and collocation solutions using the shifted Legendre spectral method for the Hilfer fractional stochastic integro-differential equations regarding stochastic... by Haneen Badawi, Omar Abu Arqub, Nabil Shawagfeh

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DetNet service share protection scheme based on SRv6 by Shuopeng LI, Juan FANG, Ken CHEN

“…To solve the problem that existing methods are difficult to achieve efficient deployment and service protection in deterministic network (DetNet), a DetNet service protection architecture based on SRv6 was proposed.By leveraging this architecture, a service-oriented DetNet protection scheme was designed and the share protection policy was formulated.With the aid of backup bandwidth share, the proposed heuristic based on shortest path optimized network resource utilization and delay.The simulation results show that the share protection algorithm achieves better performance than non-share algorithm.…”
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Optimization of Parameters of a Vertical Ground Heat Exchanger in a Geothermal Heating System by Walery Jezierski, Piotr Rynkowski

“…Only factor <i>T</i>_w (<i>X</i>₄), with such a change, caused a decrease in the thermal efficiency of the tested heat exchanger by 44.22%. The parameters of the tested element of the geothermal heating system were also optimized according to the energy criterion using a numerical method in the Matlab environment. …”
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Numerical implementation of a stochastic differential equation of motion by Saúl Moisés Torres Murga

“…In order to extract solutions from this equation, the Euler-Maruyama method was used, which was implemented computationally. …”
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Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method by Yingdong Wang, Chen Xing, Leihua Yao

“…It is often difficult for a structural safety design method based on deterministic analysis to fully and reasonably reflect the randomness of mechanical parameters, while the traditional reliability analysis method has a large calculation cost and low accuracy. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…Consequently, the proposed MARL-FOPID controller reported better disturbance-rejection performance in different working cases compared to other conventional methods.…”
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An Efficient Uncertainty-Driven Learning for Stochastic Super-Resolution by Daeyoung Han, Seongmin Hwang, Hoyeon Ahn, Moongu Jeon

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