A Lightweight, Intelligent Autonomous Exploration System for Indoor Robots Using Improved Random Walk With Back-Off Strategies by Blesson Mathews Luke, S. Abraham Sampson

“…The algorithm maintained a reliable average localization error of 0.005 m while exhibiting memory efficiency by the reduced memory usage by up to 13.7% relative to TB3. …”
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Energy management in a microgrid equipped with an electric vehicle based on the internet of things considering responsive load by Mohamad Mahdi Erfani Majd, Reza Davarzani, Mahmoud Samiei Moghaddam, Ali Asghar Shojaei, Mojtaba Vahedi

“…A novel Energy-Trading Management Algorithm (ETMA), based on the Meerkat Optimization Algorithm (MOA), is proposed to tackle the complexities of this system. …”
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Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports by Xincong Wu, Zhanzhu Li, Xiaohua Cao

“…In the simulation experiment results, the proposed algorithm outperforms A*, ACO, and IEA algorithms in optimizing path length, reducing collision points to ensure path safety, and robustness. …”
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Retrospective Illumination Correction of Retinal Images by Libor Kubecka, Jiri Jan, Radim Kolar

“…Among the tested optimizers, the gradient-based optimizer with varying step has shown to have the fastest convergence while providing the best precision. …”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…The extended search mode was refined by integrating the simplex method, while the optimization capability of the Whale Optimization Algorithm (WOA) was enhanced with Levy flight to improve step length. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…To further enhance the LSTM performance, the GWO is employed to adaptively optimize the key parameters of the LSTM. Thirdly, to fully leverage the advantages of XGBoost in handling nonlinear relationships and high-dimensional data while overcoming its complexities in parameter tuning and slower convergence, the GA is used to optimize the parameters of XGBoost. …”
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DSGD++: Reducing Uncertainty and Training Time in the DSGD Classifier through a Mass Assignment Function Initialization Technique by Aik Tarkhanyan, Ashot Harutyunyan

“…We present a method for the Dempster-Shafer Gradient Descent (DSGD) algorithm that significantly reduces training time—by a factor of 1.6—and also reduces the uncertainty of each rule (a condition on features leading to a class label) by a factor of 2.1, while preserving accuracy comparable to other statistical classification techniques. …”
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Performance analysis of secrecy rate for SWIPT in massive antenna by Hui BAO, Minmin ZHANG, Yaqing YAO, Hui WANG

“…In the multi-drop broadcast system,the existing research is to optimize the single-user security rate in the complete channel state information.In fact,it’s impossible that there exists only one user in the system.The base station often receives incomplete channel state information.Aiming at this problem,a robust beamforming scheme was proposed.In the multi-user case,considering the influence of channel estimation error on the system security rate,the particle swarm optimization algorithm was used to optimize the emission beamforming vector,artificial noise covariance and power split ratio to ensure that the user collects a certain energy while maximizing the safe transmission rate.The simulation results show that the proposed scheme is slightly lower than the security rate in the ideal case,but it is meaningful to the actual system,taking into account the existence of eavesdropping users and the estimation error.…”
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MAB-RSP: Data pricing based on Stackelberg game in MCS by Yongjiao Sun, Xueyan Ma, Anrui Han

“…Experiments demonstrate that the algorithm improves revenue while ensuring balanced benefits for all participants.…”
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Research on secure transport strategy of mobile edge computing based on deep reinforcement learning by WANG Yijun, LI Jiaxin, YAN Zhiying, LYU Jingying, QIAN Zhihong

“…Firstly, the mobile edge computing system based on unmanned aerial vehicle (UAV) was studied, which was composed of<italic> I</italic> user devices, <italic>M</italic> legal UAV (L-UAV) and <italic>N</italic> eavesdropping UAV (E-UAV). Secondly, while ensuring the unloading of L-UAV within a specified period, the multi-agent depth deterministic policy gradient (Attention-MADDPG) algorithm with the addition of attention mechanism was adopted to solve and optimize the problem with the aim of maximizing the safety unloading efficiency of the communication system. …”
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Multimodal Control by Variable-Structure Neural Network Modeling for Coagulant Dosing in Water Purification Process by Jun Zhang, Da-Yong Luo

“…This method rectifies coagulant dosage effectively while keeping valid coagulation performance. By the way, the MM-P-VSRVNN algorithm can decrease computation time and avoid overfitting learning ability. …”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…Anomaly detection (AD) is increasingly recognized as a key component for ensuring the resilience of future communication systems. While deep learning has shown state-of-the-art AD performance, its application in critical systems is hindered by concerns regarding training data efficiency, domain adaptation and interpretability. …”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…This study aims to develop a high-precision, robust torque distribution model to enhance energy utilization while addressing interference from environmental noise and extreme temperatures.MethodsA real-time torque distribution model integrates three core components: a Markov Decision Process framework transforms torque allocation into a mathematical optimization problem; the Proximal Policy Optimization algorithm enhanced with Prioritized Experience Replay dynamically generates control strategies; and Fiber Bragg Grating sensors achieve millisecond-level torque measurement by correlating shaft strain forces with wavelength shifts. …”
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Low power IoT device communication through hybrid AES-RSA encryption in MRA mode by Qiang Chang, Tianqi Ma, Wenzhong Yang

“…The enhanced RSA algorithm replaces the traditional dual-prime system with a triple-prime system, increasing the number of primes while reducing the bit length of each prime. …”
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Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control by Hongxiang Chen, Xiuli Zhang, Mingguo Zhao

“…TP-MPC is utilized to optimize the rough planning’s reference trajectory, while WBC is employed to follow the optimized trajectory. …”
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Hybrid beamforming for ISAC based on mmWave cell-free MIMO by DUO Lin, YANG Xin, REN Yong, XU Boyu

“…Two kinds of power constraints are considered in the study, and the improved orthogonal matching pursuit algorithm and the Riemann conjugate gradient algorithm are used for optimization. …”
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A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks by Man Gun Ri, Ye Song Han, Jin Pak

“…In our new algorithm, clustering and routing tree construction is performed while introducing the optimal relay transmission distance achieved by using opportunistic routing principle, and at the same time, interference-free wake up time is scheduled, which may optimize energy consumption and decrease the number of various control messages as possible to prolong the network lifetime. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…By combining MUAPs with surrogate models, SMPack effectively overcomes the black-box constraints and improves the efficiency of generating adversarial examples. Additionally, we optimize this process using a Genetic Algorithm (GA), allowing for efficient search of the perturbation space while conserving query budget. …”
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Observer-Based Sliding Mode Control for Vehicle Way-Point Tracking with Unknown Disturbances and Obstacles by Jiacheng Song, Mingjie Shen, Yanan Zhang

“…An observer compensation technique is utilized to monitor and mitigate disturbances, while sliding mode control, enhanced by a HyperSpiral algorithm, ensures accurate and stable tracking performance. …”
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Lightweight CNN-Based Visual Perception Method for Assessing Local Environment Complexity of Unmanned Surface Vehicle by Tulin Li, Xiufeng Zhang, Yingbo Huang, Chunxi Yang

“…Subsequently, this identification result can be used as feedback for the heuristic algorithm to optimize and plan the USV’s path. The simulation results indicate that the developed model achieves an 80% reduction in model size while maintaining an accuracy exceeding 90%. …”
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