An Optimization Method for Operation Adjustment of High-Speed Delayed Trains by Xiaojuan Li, Yueying Huo, Zhenying Yan, Baoming Han

“…In addition, the second model is an optimization model for operation adjustment with the least average delay time of each train at each station by updating the state matrixes of the train operation process model. …”
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Efficient LLMs Training and Inference: An Introduction by Rui Li, Deji Fu, Chunyu Shi, Zhilan Huang, Gang Lu

“…Therefore, adopting optimization strategies during the training and inference stages is essential to address these challenges. …”
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A Novel Improved Binary Optimization Algorithm and Its Application in FS Problems by Boyuan Wu, Jia Luo

“…It combines three learning strategies on the basis of the Parrot Optimizer (PO) to better ensure FS performance. …”
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Tram Whole-Train Braking Force Management Strategy Based on TCMS by XU Jie, YANG Chuan, MA Xuan

“…[Method] The design of tram braking control system is introduced, including braking system configuration, braking mode, and interactive data information. A whole-train braking force control strategy based on TCMS is put forward, including methods for collecting train running speed and load, and methods for braking control strategy and optimization. …”
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Optimizing active recovery strategies for finger flexor fatigue by Dominika Krupková, James J. Tufano, Jiří Baláš

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ATO Controller Research Based on Predictive Fuzzy Control Algorithm by LIU Jiazheng, XU Juan

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Simulation and Optimization of Metro Train Braking Rate under the Timing Condition by PAN Yang

“…Since traction consumes the main energy in metro operation, it is necessary to conduct a study on the optimization of traction energy consumption. ［Method］ In consi-deration of the low train braking rate in the process of metro design and operation, an energy-saving operation strategy is proposed by appropriately increasing the train braking rate and lowering the maximum cruising speed under fixed interval running time condition, that is, under the timing condition. …”
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Neural-Driven heuristic for strip packing trained with Black-Box optimization by Mariusz Kaleta, Tomasz Śliwiński

“…Instead of relying on static heuristic rules, our approach adapts to the characteristics of each problem instance, enabling more efficient and effective packing strategies. To train the neural network, we employ the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), a state-ofthe- art derivative-free optimization method. …”
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Joint Optimization of Resource Allocation and Task Offloading Strategies in Multi-Cell Dynamic MEC Systems Using Multi-Agent DRL by Yuntao Hu, Ming Chen, Haowen Sun, Yinlu Wang, Yihan Cang

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Application of Regenerative Braking with Optimized Speed Profiles for Sustainable Train Operation by Leon Allen, Steven Chien

“…Regenerative braking captures and reuses the braking energy of the train and could shorten travel time but reduces the time available for coasting, indicating a tradeoff between the two strategies. …”
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Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

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Coasting-cruising Combined Control Strategy Based on Train Energy-efficient Operation by GAO Hao, CHAI Juan, LING Xiaoque, XU Haigui

“…The genetic algorithm is used to calculate respectively the train energy-efficient optimized operation curves under the coasting-cruising combined control strategy and the multiple coasting control strategy. …”
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Train adaptive energy saving strategy based on iterative induced genetic algorithm by MEI Wenqing, SHI Ke, ZHANG Zhengfang

“…The objective function was solved under manipulation characteristic constraints to achieve optimal energy-saving planning. Firstly, the optimization objective was designed as several sub-intervals based on the ramp of the train route. …”
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Driving Strategy Using an Improved Ant Colony System for Energy-Efficient Train by Chengda Yang, Kun Miao, Jieyuan Wang

“…Optimal energy-efficient train operation optimization is one of the widely studied areas in transportation science, which can significantly reduce energy consumption that accounts for a large proportion of operating costs. …”
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Research on Active–Passive Training Control Strategies for Upper Limb Rehabilitation Robot by Yongming Yang

“…Therefore, this paper conducts research on active–passive training control strategies for an upper limb rehabilitation robot. …”
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Optimization Strategies in Quantum Machine Learning: A Performance Analysis by Nouf Ali AL Ajmi, Muhammad Shoaib

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Investigating Recovery Strategies to Optimize Performance and Well-being in Basketball by Marco Pernigoni

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Optimal Control Strategy of Coupler Force in Urban Rail Transit by JING Feiyao, XU Gang, YIN Jian, SHEN Jianhao

“…Experimental results showed that under the precondition of satisfy the standard of metro vehicle running, starting and accelerating the train in the constant force and constant speed operation, the optimal control strategy was not train traction evenly distributed control strategy. …”
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An Optimal Reconfiguration Strategy of Microgrid Cluster Based on Vulnerability Assessment by LIU Haocheng, DING Xiying

“…This paper presents an optimal reconfiguration strategy of micro-grid cluster based on vulnerability assessment. …”
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Optimizing Federated Learning With Aggregation Strategies: A Comprehensive Survey by Naeem Khan, Shibli Nisar, Muhammad Asghar Khan, Yasar Abbas Ur Rehman, Fazal Noor, Gordana Barb

“…This article provides a comprehensive survey of aggregation strategies in federated learning (FL). This decentralized machine learning (ML) paradigm enables multiple clients to collaboratively train models without sharing their local datasets. …”
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