Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Building on this, the cost function is integrated with lateral offset and heading offset information, combined with the obstacle avoidance penalty function, and an anti-disturbance model predictive control scheme is constructed by solving the nonlinear constrained optimization problem online. …”
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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Building on this, the cost function is integrated with lateral offset and heading offset information, combined with the obstacle avoidance penalty function, and an anti-disturbance model predictive control scheme is constructed by solving the nonlinear constrained optimization problem online. …”
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Research on the Stability of Express Delivery Supply Chain Based on Risk Propagation Model ------ Case Studies of SF Express and JD Logistics by Fan Yunhui

“…Based on the research results, optimization strategies such as dynamic path optimization algorithms and blockchain-based information isolation mechanisms are proposed, providing theoretical tools and practical references for risk prevention and control in the express delivery industry.…”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Adaptive average arterial pressure control by multi-agent on-policy reinforcement learning by Xiaofeng Hong, Walid Ayadi, Khalid A. Alattas, Ardashir Mohammadzadeh, Mohamad Salimi, Chunwei Zhang

“…Abstract The current research introduces a model-free ultra-local model (MFULM) controller that utilizes the multi-agent on-policy reinforcement learning (MAOPRL) technique for remotely regulating blood pressure through precise drug dosing in a closed-loop system. …”
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Innovative multi-class segmentation for brain tumor MRI using noise diffusion probability models and enhancing tumor boundary recognition by Zengxin Liu, Caiwen Ma, Wenji She, Meilin Xie

“…Addressing the escalating demand for precise diagnostics, this research focuses on the challenges of multi-class segmentation in MRI. The proposed algorithm integrates diffusion models, capitalizing on their efficacy in capturing microstructural details, emphasizing the intricacies of human anatomy and tissue variations that challenge segmentation algorithms. …”
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Adaptive control for vehicle formation movement with multiple sensors by TANG Mingzhu, XIANG Guoliang, SHI Hongwei, GUO Shenghui

“…The adaptive motion algorithm based on predetermined motion trajectories is studied in this paper, addressing the problem of vehicle formation with multiple sensors. …”
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Estimation of Leaf Chlorophyll Content of Maize from Hyperspectral Data Using E2D-COS Feature Selection, Deep Neural Network, and Transfer Learning by Riqiang Chen, Lipeng Ren, Guijun Yang, Zhida Cheng, Dan Zhao, Chengjian Zhang, Haikuan Feng, Haitang Hu, Hao Yang

“…Combining the E2D-COS feature selection with TL and DNN significantly improves the estimation accuracy: the R² of the proposed Maize-LCNet model is improved by 0.06–0.11 and the RMSE is reduced by 0.57–1.06 g/cm compared with LCNet-field. …”
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RecompGPT: Generative Pre-Trained Transformers-Assisted Interactive Human Gaze Pattern Learning and Distribution Modeling for Scene Recomposition by Wang Shang, Nassiriah Binti Shaari, Nur Sauri Bin Yahaya, Liu Hao

“…Afterward, these GSPs are refined via a multi-layer aggregation algorithm that encodes deep feature representations into a Gaussian Mixture Model (GMM) to model the distribution of human gaze patterns. …”
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Machine Learning and Metaheuristics Approach for Individual Credit Risk Assessment: A Systematic Literature Review by Álex Paz, Broderick Crawford, Eric Monfroy, José Barrera-García, Álvaro Peña Fritz, Ricardo Soto, Felipe Cisternas-Caneo, Andrés Yáñez

“…Although no unified experimental comparison was conducted due to heterogeneity in study protocols, this structured summary reveals consistent trends in algorithm effectiveness and evaluation practices. The review concludes with practical recommendations and outlines future research directions to improve fairness, scalability, and real-time application in credit risk modeling.…”
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Power Load Data Completion Method Based on Integrated Graph Convolutional Variational Transformer by YAN Li, HU Hailin, SHI Lei, WU Qinzheng, LÜ Tianguang, XU Yingdong, ZHANG Wenbin, WANG Gaozhou

“…The raw data are processed by the GCN to learn spatial features and deeply mine spatial dependencies； the hidden layer data are reconstructed by the VAE to more effectively restore data distribution characteristics； and the temporal autocorrelation information of the sequence is mined based on the Transformer model. In addition， an improved whale optimization algorithm （WOA） is introduced to optimize the network model hyperparameters and improve the completion accuracy and applicability of the model. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…An attention mechanism is added to focus on the most important features,improving the prediction accuracy of the model. Finally,the improved dung beetle optimization (IDBO) algorithm is used to optimize the hyper-parameters of the model. …”
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Review and Prospects of Artificial Intelligence Technology in Virtual Power Plants by Xinxing Liu, Ciwei Gao

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Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening by Zhuo Zhao, Xiaoxu Liu, Yonghui Guan, Chunfang Li, Zheng Wang

“…Purpose This study introduces a Pyramid Scene Parsing Network (PSPNet) model to predict PE, aiming to improve early risk assessment using cfRNA profiles. …”
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Dry-Type Air-Core Series Reactor Turn-to-Turn Short Circuit Fault Detection Method Based on Multi-Parameter Data Fusion by WANG Yin, WANG Yuanyuan, CAO Chengjun, ZHANG Lizhi, YIN Youpeng, JI Hongzhen, DOU Di

“…Subsequently， the denoised features with high saturation are input into the k-nearest neighbors （KNN） algorithm to construct a fault identification and classification model. …”
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A Full-Life-Cycle Modeling Framework for Cropland Abandonment Detection Based on Dense Time Series of Landsat-Derived Vegetation and Soil Fractions by Qiangqiang Sun, Zhijun You, Ping Zhang, Hao Wu, Zhonghai Yu, Lu Wang

“…The parameters of the optimization model (fitting type, change magnitude, start timing, and change duration) are subsequently integrated to develop a rule-based hierarchical identification scheme for cropland abandonment based on these complex scenarios. …”
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A Dynamic Precision Evaluation System for Physical Education Classroom Teaching Behaviors Based on the CogVLM2-Video Model by Chao Liu, Fan Yang, Chengyu Ge, Zhiyu Shao

“…The platform layer manages data processing and storage, ensuring integrity and security for long-term evaluation. The model layer focuses on behavior recognition and analysis, employing advanced algorithms for precise interpretation of teaching behaviors. …”
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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…The system is designed to integrate advanced AI techniques, providing an innovative approach to pose recognition that leverages several sophisticated machine learning models and algorithms to enhance performance. The pre-processing stage involves applying a Wiener Filter (WF) for effective noise removal, ensuring that the data is clean and ready for analysis. …”
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Enhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection by Pramodh Krishna D., E. Sandhya, Khaja Shareef Sk, Srihari Varma Mantena, Venkata Subbaiah Desanamukula, Ch Koteswararao, Srinivasa Rao Vemula, Maruthi Vemula

“…This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs. To optimize the model’s efficiency, a unique DECEHGS algorithm combining Differential Evolution and Evolutionary Population Dynamics techniques is employed, enhancing both convergence and performance. …”
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Three-Dimensional Imaging of High-Contrast Subsurface Anomalies: Composite Model-Constrained Dual-Parameter Full-Waveform Inversion for GPR by Siyuan Ding, Deshan Feng, Xun Wang, Tianxiao Yu, Shuo Liu, Mengchen Yang

“…However, full-waveform inversion (FWI) for GPR data struggles to simultaneously reconstruct high-resolution 3D images of both permittivity and conductivity models. Considering the magnitude and sensitivity disparities of the model parameters in the inversion of GPR data, this study proposes a 3D dual-parameter FWI algorithm for GPR with a composite model constraint strategy. …”
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