Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…These computed paths are then used to define the mean control input for the MPPI algorithm, which performs localized optimization while adhering to the terrain-aware trajectory. …”
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Multi-Armed Bandit Approaches for Location Planning with Dynamic Relief Supplies Allocation Under Disaster Uncertainty by Jun Liang, Zongjia Zhang, Yanpeng Zhi

“…We introduce a multi-armed bandit algorithm, named the Geometric Greedy algorithm, to optimize transfer station planning while accounting for subsequent dynamic relief supply distribution and allocation in a stochastic environment. …”
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Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines by Yufeng Xiao, Wei Zhou, Boyu Luan, Keyi Yang, Yuqing Yang

“…Results demonstrate that both the basic genetic algorithm and the adaptive genetic algorithm effectively achieve truck transportation scheduling. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Simulation experiments using the REMUS 100 AUV model show that DVFH+ can provide a smoother and more feasible obstacle avoidance route, making it suitable for AUV obstacle avoidance in complex environments while effectively preventing issues such as detouring and planning failure caused by improper threshold settings in the original algorithm.…”
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Research on Stability Optimization for Automatic Train Operation of Heavy-haul Trains of Baoshen Railway by FU Shangyuan

“…This algorithm features a multi-particle model and a train state evaluation model for heavy-haul trains, evaluating the development trend of train states while incorporating constraints related to the loading/unloading slope in levels. …”
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Metaheuristic-Based Cepstral Sensing Technique for Prolonging Network Lifetime and Mitigating Primary User Emulation Attacks in Cognitive Radio Sensor Network by V. Abilasha, A. Karthikeyan

“…Whale optimisation algorithm maintains network performance and energy efficiency while refining sensing parameters and enhancing decision-making. …”
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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

“…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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Evaluation of Multi-Class Classification Performance Lung Cancer Through K-NN and SVM Approach by Muh. Indra Endriartono Saputra Troy, Sitti Rahmah Jabir, Siska Anraeni

“…In an effort to improve diagnosis and treatment, this study proposes an approach for multiclass performance evaluation using K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms based on 2024 data. in this study KNN is implemented conventionally while SVM applies 2 kernel processes, namely Linear and Polynominal. …”
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Methods Research on Correction for Intracranial Metal Artifacts Based on Prior Image Utilization by Zonggui CHEN, Ningning WEI, Zhoufan LI, Guihong PAN, Minjiang HUANG

“…Conclusion: This algorithm effectively suppresses metal artifacts while preserving image edge information.…”
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Short time solar power forecasting using P-ELM approach by Shuqi Shi, Boyang Liu, Long Ren, Yu Liu

“…This paper proposes an accurate short-term solar power forecasting method using a hybrid machine learning algorithm, with the system trained using the pre-trained extreme learning machine (P-ELM) algorithm. …”
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Enhancing Spreading Factor Assignment in LoRaWAN with a Geometric Distribution Approach for Practical Node Distributions by Phanupong Tempiem, Rardchawadee Silapunt

“…While the GD algorithm consistently demonstrated superior DER values across varying coverage areas and payload sizes, it incurred a slight increase in energy consumption due to node allocations to higher SFs. …”
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GTrXL-SAC-Based Path Planning and Obstacle-Aware Control Decision-Making for UAV Autonomous Control by Jingyi Huang, Yujie Cui, Guipeng Xi, Shuangxia Bai, Bo Li, Geng Wang, Evgeny Neretin

“…Experimental results in the AirSim drone simulation environment demonstrate that compared to PPO and SAC algorithms, GTrXL-SAC achieves more precise policy exploration and optimization, enabling superior control of drone velocity and attitude for stabilized flight while accelerating convergence speed by nearly 20%.…”
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning by Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo

“…A Markov Decision Process (MDP) is conceived, where the time horizon includes multiple charging and operating periods in a day, while each period is further divided into multiple time steps. …”
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Three-Dimensional UAV Path Planning Based on Multi-Strategy Integrated Artificial Protozoa Optimizer by Qingbin Sun, Xitai Na, Zhihui Feng, Shiji Hai, Jinshuo Shi

“…Second, in the algorithm’s autotrophic foraging stage, we design a dynamic optimal leadership mechanism, which accelerates the convergence speed while ensuring robust exploration capability. …”
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Model split-based data privacy protection method for federated learning by CHEN Ka

“…The strategy combines leak loss of local private data and model accuracy loss that enhances privacy while maintaining model accuracy. To evaluate the proposed BLDP algorithm, experiments were conducted on four commonly benchmarked datasets and the leakage loss and model accuracy were analyzed. …”
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Flow-network based auto rescale strategy for Flink by Ziyang LI, Jiong YU, Chen BIAN, Yitian ZHANG, Yonglin PU, Yuefei WANG, Liang LU

“…In order to solve the problem that the load of big data stream computing platform is increasing with fluctuation while the cluster was not able to rescale efficiently,the Flow-network based auto rescale strategy for Flink was proposed.Firstly,the flow-network model was set up and the capacity of each edge that was calculated by self-learning algorithm.Secondly,the bottleneck of the cluster was acquired by maximum-flow algorithm and the resource rescheduling plan was drawn up.Finally,the resource rescheduling plan was executed and the stateful data was migrated efficiently by the data migration algorithm based on the strategy of data partitioning by bulk and bucket.The experimental results show that the strategy can effectively provide performance promotion in the application with complex stateful data.It improved the throughput of the cluster and reduced the time overhead of the data migration on the premise of satisfying the latency constrain of the application,which means that the strategy promotes the scalability of the cluster efficiently.…”
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Performance Analysis of a Wind Turbine Pitch Neurocontroller with Unsupervised Learning by J. Enrique Sierra-García, Matilde Santos

“…The controller is based on a radial basis function (RBF) network with unsupervised learning algorithm. The RBF network uses the error between the output power and the rated power and its derivative as inputs, while the integral of the error feeds the learning algorithm. …”
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Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
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Energy-efficient and privacy-preserving spatial range aggregation query processing in wireless sensor networks by Liang Liu, Zhenhai Hu, Lisong Wang

“…The algorithm does not rely on the pre-established topology but considers only the query area that the user is interested in, abandoning all nodes to participate in distributing the query messages while gathering the sensory data in the query range. …”
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Sensor Clustering and Sensing Technology for Optimal Throughput of Sensor-Aided Cognitive Radio Networks Supporting Multiple Licensed Channels by Thanh-Tung Nguyen, Insoo Koo

“…To do this, we formulate the throughput maximization problem as a mixed-integer nonlinear programming and utilize the Branch and Bound algorithm to solve it. We also propose an heuristic algorithm which can provide similar performance to that of the Branch and Bound algorithm while reducing computation complexity significantly.…”
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