Model‐Free Deep Reinforcement Learning with Multiple Line‐of‐Sight Guidance Laws for Autonomous Underwater Vehicles Full‐Attitude and Velocity Control by Chengren Yuan, Changgeng Shuai, Zhanshuo Zhang, Jianguo Ma, Yuan Fang, YuChen Sun

“…This framework enables seamless switching among guidance modes, such as waypoint following, path following, and trajectory tracking, to achieve optimal attitude control. For comprehensive control of roll, pitch, yaw, and longitudinal velocity, an augmented‐twin delayed deep deterministic policy gradient (A‐TD3) algorithm streamlines the training of the control agent. …”
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Toward edge-computing-enabled collision-free scheduling management for autonomous vehicles at unsignalized intersections by Ziyi Lu, Tianxiong Wu, Jinshan Su, Yunting Xu, Bo Qian, Tianqi Zhang, Haibo Zhou

“…Second, this problem is solved with low complexity by the Edge Intelligence Optimal Entry Time (EI-OET) algorithm based on edge-cloud computing power support. …”
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Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles by Xianjian Jin, Huaizhen Lv, Yinchen Tao, Jianning Lu, Jianbo Lv, Nonsly Valerienne Opinat Ikiela

“…The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with a deep deterministic policy gradient (DDPG)-based deep reinforcement learning (DRL) algorithm for dynamic optimization of controller parameters to improve tracking accuracy and robustness. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…The grayscale banding is eliminated by incorporating a visual optimization strategy based on image gradients. Maximum Histogram Equalization (MHE) is used to achieve high contrast while maintaining fidelity to the original content. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…For instance, understanding gas emissions from crops can help farmers optimize their activities, reducing fertilizer and pesticide use while improving yields. …”
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Deep learning-based phase demodulation for distributed acoustic sensor by Yiming Tang, Kewei Liu, Chen Liu, Haiyong Wu, Rugang Wang, Mengmeng Chen, Fei Xu

“…Experimental results demonstrate that the proposed method significantly enhances processing speed while maintaining accuracy comparable to traditional demodulation algorithms. …”
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A Novel PAPR in OTFS Systems Through ISSA-PTS and ISPR Techniques by Gerges Mansour Salama, Amira A. Mohamed, Aziza I. Hussein, M. Mourad Mabrook

“…The hybrid ISSA-PTS approach optimizes phase rotations to reduce PAPR, while the ISPR technique further enhances PAPR reduction by iteratively rotating sub-block phases without compromising BER. …”
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Nonlinear Model Predictive Control for Trajectory Tracking of Omnidirectional Robot Using Resilient Propagation by Mahmoud El-Sayyah, Mohamad R. Saad, Maarouf Saad

“…This paper proposes an enhanced Nonlinear Model Predictive Control (NMPC) framework that incorporates a robust, convergent variant of the resilient propagation (RPROP) algorithm to efficiently solve the Nonlinear Optimization Problem (NOP) in real time. …”
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Research on Iterative Learning Method for Lower Limb Exoskeleton Rehabilitation Robot Based on RBF Neural Network by Jing Li, Huimin Jiang, Moyao Gao, Shuang Li, Zhanli Wang, Zaixiang Pang, Yang Zhang, Yang Jiao

“…MATLAB 2021 simulations demonstrate the proposed algorithm’s superior trajectory tracking performance compared to conventional sliding mode control, effectively eliminating control chattering. …”
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A Blockchain-Based Secure Distributed Authentication Scheme for Internet of Vehicles by Zhanfei Ma, Jing Jiang, Hui Wei, Bisheng Wang, Wenli Luo, Haoye Luo, Dongxiang Liu

“…Second, in the IoV authentication process, smart contract technology is used to achieve automatic triggering of the authentication process, and an optimized Practical Byzantine Fault Tolerant Consensus (PBFT) algorithm is designed to add the authentication information to the blockchain ledger so that the authentication results can be reused. …”
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Handover Strategy for LEO Satellite Networks Using Bipartite Graph and Hysteresis Margin by Sahar Eydian, Maryam Hosseini, Gunes Karabulut Kurt

“…The proposed approach utilizes the Kuhn-Munkres (KM) algorithm to achieve optimal matching with maximum weight, thereby ensuring efficient load distribution and high-quality communication. …”
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Experimental study on mechanical properties of triaxial geogrid reinforced marine coral sand-clay mixture based on 3D printing technology by Danda Shi, Kaiwei Xu, Zhiming Chao, Zhiming Chao, Peng Cui, Peng Cui

“…Based on the experimental results, a dataset was established, while a novel machine learning model named GP-BPNN was proposed, integrating genetic algorithm (GA), particle swarm optimization (PSO), and backpropagation neural network (BPNN). …”
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A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
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Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI by Yanan Li, Jingfa Yao, Wenhui Yang, Zhao Wei, Peng Luan, Guifa Teng

“…The structural T2 relaxation inversion was refined by integrating an ACS-CIPSO algorithm. This approach addresses the challenge of low signal-to-noise ratios in multi-echo MRI images from low-field equipment by introducing an innovative solution that effectively reduces voxel noise while retaining structural relaxation variability. …”
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Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization by Hua Huang, Haiyan Shao, Yifan Wang, Lili Ge

“…The DRPS model, optimized by the StepCox[backward] algorithm, demonstrated robust prognostic accuracy across four validation cohorts (mean C-index = 0.658). …”
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Efficient Positive Semidefinite Matrix Approximation by Iterative Optimisations and Gradient Descent Method by Vali Asimit, Runshi Wang, Feng Zhou, Rui Zhu

“…Experiments on randomly generated data show that this method enjoys better resilience to noise while maintaining good accuracy. For example, in our experiments with noised data, the iterative quadratic programming algorithm performs best in more than 41% to 67% of the samples when the standard deviation of noise is 0.02, and the gradient descent method performs best in more than 70% of the samples when the standard deviation of noise is 0.2. …”
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A Target Near-Field Scattering Measurement Technique Utilizing 3D Near-Field Imaging via Cylindrical Scanning by Zongkai Yang, Jingcheng Zhao, Weikang Si, Changyu Lou, Xin Zhao, Jungang Miao

“…To resolve this matter, we propose a hybrid 3D imaging algorithm that is optimized for cylindrical sampling and operates in both the wavenumber domain and time domain (WDTD). …”
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Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures by Shahram Lotfi, Shahin Ahmadi, Alla P. Toropova, Andrey A. Toropov

“…This study aimed to develop a QSPR model for predicting the impact sensitivity of 404 nitro compounds using the Monte Carlo algorithm implemented in CORAL-2023 software. The Simplified Molecular Input Line Entry System (SMILES) was employed to represent the molecular structures, while correlation weight descriptors were computed. …”
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Practical DU-CU Placement in an Enhanced Mobile BroadBand Request During 5G Traffic by Ange Joel Nounga Njanda, Joao Filipe Muchanga, Hojjat Baghban, Karcius Day R. Assis

“…The objective is to identify the optimal candidate sites for deploying the DU and CU functions to ensure a continuous service path from the RU to the DC. …”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. …”
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