H∞ Consensus Design and Online Scheduling for Multiagent Systems with Switching Topologies via Deep Reinforcement Learning by Haoyu Cheng, Ruijia Song, Linpeng Xu, Di Zhang, Shengli Xu

“…Moreover, the online scheduling is formulated as a Markov decision process, and the deep deterministic policy gradient (DDPG) algorithm in the framework of actor-critic is proposed for the compensation of disturbance to explore optimal control policy. …”
Get full text

Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

“…Then, four machine learning algorithms and three deep learning networks are evaluated to determine the best predictive model. …”
Get full text

Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…We incorporated band selection techniques, including the Norris derivative and the Successive Projections Algorithm (SPA), and optimized the data processing workflow. …”
Get full text

Prediction of cutting depth in abrasive water jet machining of Ti-6AL-4V alloy using back propagation neural networks by Yakub Iqbal Mogul, Ibtisam Mogul, Jaimon Dennis Quadros, Ma Mohin, Abdul Aabid, Muneer Baig, Mohammad Abdul Malik

“…The results showed that as the depth of cut was small, i.e., ranging from 3 mm to 5 mm, the algorithm was unable to predict the optimized parameters, however, the prediction improved as the depth of cut increased. …”
Get full text

Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…By establishing coherent relationships between node representations and community structures, we optimize both the Convex-NMF-based representation learning model and the evolutionary clustering-based TCD model within a unified framework. …”
Get full text

Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
Get full text

Real-time monitoring of soil moisture in cotton fields using electromagnetic induction technology by Yang Gao, Quanze Hu, Jiaojiao Hui, Lin Chang, Mei Zeng, Qingsong Jiang

“…The Kalman filter algorithm was used to improve the accuracy of the model. …”
Get full text

Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
Get full text

Knowledge Discovery Using Clustering Methods in Medical Database: A Case Study for Reflux Disease by Fatma Rıdaouı, Yunus Doğan

“…In the tests, it was observed that the most successful algorithm in terms of the structure of the data was KMeans, and a set of remarkable 27 rules according to the optimal Sum of Square Error value was obtained.…”
Get full text

Research on economic dispatching strategy for active distribution network considering high penetration of renewable energy source by ZHANG Yu, YUAN Bo, HUANG Shicheng, SHI Jinyue, AN Yichen

“…The effectiveness of the proposed strategy and the superiority of similar algorithms are validated through using an improved IEEE 33-node test system.…”
Get full text

Advances in the application of machine learning technology in the field of environmental health by ZHENG Yu, LI Cheng, HU Guiping, JIA Guang

“…Among them, advanced machine learning (ML) algorithms can reveal laws that are difficult for humans to detect, showing important potential in biomarker identification, disease prevention, and environmental engineering optimization. …”
Get full text

Statistical and Machine Learning Classification Approaches to Predicting and Controlling Peak Temperatures During Friction Stir Welding (FSW) of Al-6061-T6 Alloys by Assad Anis, Muhammad Shakaib, Muhammad Sohail Hanif

“…Some simulations showed temperatures exceeding the material’s melting point, indicating the need for improved thermal control. This was achieved by using three machine learning (ML) algorithms, i.e., Logistic Regression, k-Nearest Neighbors (k-NN), and Naive Bayes. …”
Get full text

Analyzing Method of the Absorption Capability of New Energy in Distribution Network with Consideration of Regional Self-discipline and Absorption Quality by Yan CHEN, Wei JIN, Wenbin WANG, Huibin LI, Shengfeng HAN, Kai JIA

“…Firstly, the strategy for implementing the self-discipline operation of the distribution network was unveiled, and the performance indices of self-discipline operation capability were created. Then, the optimal allocation model for the new energy absorption capability of the distribution network was constructed, and the operation behavior model of the distribution network satisfying self-discipline constraints was built based on energy storage, flexible load, and network reconstruction, and solved by the genetic algorithm. …”
Get full text

Secondary System Fault Detection Method Based on Association Rules and Reconstruction Error by Yang WANG, Weidong MA, Jiming LIU, Boshi WANG, Kai YAO, Wei HAN, Juan YU

“…Finally, the ensemble learning model is optimized to improve the accuracy of secondary equipment anomaly warning. …”
Get full text

Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Finally, the global model parameters are fed back to the vehicles to further optimize the local resource allocation strategy, thus improving the system spectrum efficiency. …”
Get full text

Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
Get full text

Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…We proposed the PF-YOLO model and conducted experimental comparisons with several excellent models, achieving improvements in mAP of 5.5%, 6.8%, 2.5%, 2.1%, 5.7%, 2.9%, 1.5%, and 3.4% compared to Yolov5s, Yolov5l, Yolov5s-p6, Yolov5l-p6, Tph-Yolov5, Yolov8n, Yolov8s, and Yolov9c, respectively. …”
Get full text

Apple Pest and Disease Detection Network with Partial Multi-Scale Feature Extraction and Efficient Hierarchical Feature Fusion by Weihao Bao, Fuquan Zhang

“…To address this issue, this study proposes an improved pest and disease detection algorithm, YOLO-PEL, based on YOLOv11, which integrates multiple innovative modules, including PMFEM, EHFPN, and LKAP, combined with data augmentation strategies, significantly improving detection accuracy and efficiency in complex environments. …”
Get full text

RSWD-YOLO: A Walnut Detection Method Based on UAV Remote Sensing Images by Yansong Wang, Xuanxi Yang, Haoyu Wang, Huihua Wang, Zaiqing Chen, Lijun Yun

“…In this paper, we propose a walnut detection method based on UAV (UAV means Unmanned Aerial Vehicle) remote sensing imagery to improve the walnut yield prediction accuracy. Based on the YOLOv11 network, we propose several improvements to enhance the multi-scale object detection capability while achieving a more lightweight model structure. …”
Get full text

A novel hybrid nonlinear control of four switch buck-boost converter feeding constant power load in fuel cell-based DC microgrid by Hafiz Mian Muhammad Adil, Hassan Abbas Khan

“…Controller parameters are optimized using the slime mould algorithm, minimizing the integral time absolute error (ITAE) to address both transient and steady-state behavior. …”
Get full text