IEEE Transactions on Cybernetics最新文献

{"title":"IEEE Transactions on Cybernetics","authors":"","doi":"10.1109/TCYB.2025.3559264","DOIUrl":"10.1109/TCYB.2025.3559264","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"C3-C3"},"PeriodicalIF":9.4,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10974925","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Cybernetics","authors":"","doi":"10.1109/TCYB.2025.3559262","DOIUrl":"10.1109/TCYB.2025.3559262","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 5","pages":"C4-C4"},"PeriodicalIF":9.4,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10974961","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143866641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyper-Heuristic Optimization Using Multifeature Fusion Estimator for PCB Assembly Lines With Linear-Aligned-Heads Surface Mounters","authors":"Guangyu Lu, Huijun Gao, Zhengkai Li, Xinghu Yu, Tong Wang, Jianbin Qiu, Juan J. Rodríguez-Andina","doi":"10.1109/tcyb.2025.3556512","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3556512","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"19 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast UAV Object-Searching in Large-Scale and Complex Environments","authors":"Hai Lin;Xinsong Yang;Guanghui Wen;Wei Xing Zheng","doi":"10.1109/TCYB.2025.3556744","DOIUrl":"10.1109/TCYB.2025.3556744","url":null,"abstract":"Autonomous object-searching is crucial for various applications of unmanned aerial vehicles (UAVs). Considering the fact that existing autonomous exploration methods either focus only on maximizing the exploration of unknown areas or suffer from insufficient searches due to repeated and unnecessary exploration, this article introduces an effective object-searching strategy for UAVs in large-scale and complex environments. A novel method is proposed to empower UAVs with the capability to conduct fast, secure, and efficient searches for interested objects in large-scale and complex environments. A Kalman filter-based YOLO algorithm is first proposed to achieve robust object position estimation in cluttered and occlusion-prone scenarios, and a mode-based method is then introduced to conduct a computationally efficient viewpoint generation. A hierarchical searching method is proposed, which not only can increase computational and search efficiency but also can leverage frontier data for search-planning, including coarse global searching paths and optimizing local refined searching trajectories. Experimental results in six different environments indicate that our proposed method outperforms existing techniques in terms of both reduced searching times and computing time. Moreover, the effectiveness of the proposed method is substantiated in various real-world scenarios.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 6","pages":"2993-3004"},"PeriodicalIF":9.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fixed/Prescribed-Time Synchronization and Energy Consumption for Kuramoto-Oscillator Networks","authors":"Zhenfeng Ma;Dongbing Tong;Qiaoyu Chen;Wuneng Zhou","doi":"10.1109/TCYB.2025.3556103","DOIUrl":"10.1109/TCYB.2025.3556103","url":null,"abstract":"To evaluate the energy-saving effect of the controller, obtaining upper bounds on energy consumption and control time has become a worthwhile and meaningful issue to study. This article mainly discusses three contents about the Kuramoto oscillator network, including fixed-time synchronization (FxTS), prescribed-time synchronization (PTS), and energy consumption estimation. First, to reach FxTS, two sufficient conditions are proposed to guarantee that the Kuramoto oscillator network can reach fixed-time phase agreement and frequency synchronization. Unlike finite/fixed-time controllers, the prescribed-time controller in this article includes a time-varying function term, which is essential to ensure that the system achieves the prescribed-time phase agreement and frequency synchronization. At the same time, the setting-time for PTS is independent of the system initial values or controller parameters, which expands the application prospects of the system. Then, with limited setting-time as a premise, the energy consumed during the fixed/prescribed-time control process is obtained, which helps to evaluate the working time of the system. Finally, an example of a 5-node network is used to illustrate the effectiveness of FxTS and PTS in Kuramoto-oscillator networks.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 7","pages":"3379-3389"},"PeriodicalIF":9.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward In-Depth Mastery of Statistical Properties: Novel Stationary Moment Analysis With Application to Continuous Industrial Anomaly Detection","authors":"Siwei Lou;Chunjie Yang;Weibin Wang;Hanwen Zhang;Yuchen Zhao;Ping Wu","doi":"10.1109/TCYB.2025.3556598","DOIUrl":"10.1109/TCYB.2025.3556598","url":null,"abstract":"Anomaly detection is a cornerstone of industrial safety, enabling real-time monitoring of process operations by identifying deviations from normal conditions through statistical analysis. In real-world industrial scenarios, the nonstationary properties of multivariate time-series data present a common and substantial challenge. Existing methods for extracting stationary sources <inline-formula> <tex-math>$(mathcal {SS}s)$ </tex-math></inline-formula> mainly rely on weak stationarity (i.e., mean and variance), but their performance is limited by the long-tailed distributions common in industrial datasets. Higher-order moments, in contrast, provide a more comprehensive statistical description, capturing complex data characteristics that the mean and variance overlook. To bridge this significant gap, we propose a continuous stationary moment analysis (Co-SMA) anomaly detection framework. Its core innovation is the SMA algorithm, which introduces a novel objective function to minimize cumulative sum of the differences in multiorder moments between each epoch and the overall data, effectively fulfilling the <inline-formula> <tex-math>$mathcal {SS}$ </tex-math></inline-formula> estimation task. Furthermore, to overcome the inefficiencies of traditional model updating methods, we develop an event-triggered model updating framework based on the model bias index and first-order perturbation theory. Within this framework, we introduce a convex hull coverage metric, which enables the model to be adjusted efficiently according to the data distribution drift. The framework also incorporates iterative refinement of detection statistics and thresholds, establishing a dynamic adjustment mechanism that ensures optimal performance across diverse operating conditions. The theoretical basis of Co-SMA’s properties is rigorously established. Experimental evaluations on numerical simulations and real-world datasets from the ironmaking process demonstrate Co-SMA’s superior capabilities in <inline-formula> <tex-math>$mathcal {SS}$ </tex-math></inline-formula> estimation and anomaly detection.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 7","pages":"3417-3430"},"PeriodicalIF":9.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Secure State Estimation and Attack Detection for Dynamical Systems With Attacks on a Time-Varying Sensor Set","authors":"Guangran Lyu, Xiao He","doi":"10.1109/tcyb.2025.3557269","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3557269","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"32 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Group Role Three-Way Assignment for Managing Uncertainty in Role Negotiation","authors":"Shiyu Wu;Shenglin Li;Haibin Zhu;Rui Chen;Libo Zhang","doi":"10.1109/TCYB.2025.3558402","DOIUrl":"10.1109/TCYB.2025.3558402","url":null,"abstract":"Role-based collaboration (RBC) is an innovative collaborative approach designed to enhance collaboration. Role negotiation (RN) is a critical step in RBC, during which the role set and the number of agents required for each role, i.e., role requirements, are determined. This process establishes the foundational input for group role assignment (GRA), where roles are assigned to agents to optimize group performance. Uncertainties in RN, such as task volume fluctuations, create dynamic agent requirements. However, existing RBC models typically assume RN to be static, thus failing to adequately address the substantial challenges. Three-way decision (3WD) is a robust decision-making methodology well-suited for managing uncertainty. To address the uncertainties in role requirements, this article introduces truncated discrete distribution to quantify role requirements, and presents a novel group role three-way assignment (GR3A) model. Compared with traditional RBC, our model offers an additional variable partial substitute choice that offers agents little salary during nonengagement periods but can transition to full involvement as required according to the prior agreement. GR3A is a dual-objective nonlinear optimization problem, for which a linearization strategy is proposed to achieve the optimal resolution. Additionally, sufficient and necessary conditions for these assignment problems are put forward to enhance the efficacy of the proposed solutions. To our knowledge, this study innovatively introduces a truncated discrete distribution and 3WD into the RBC framework. Empirical validation through simulations demonstrates the effectiveness and efficacy of the proposed method within the RBC context.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 6","pages":"2924-2936"},"PeriodicalIF":9.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Constructive Approach for Neural Network Approximation Sets in Adaptive Control of Strict-Feedback Systems","authors":"Yu-Fa Liu, Yong-Hua Liu, Jin-Wa Wu, Ante Su, Chun-Yi Su, Renquan Lu","doi":"10.1109/tcyb.2025.3559235","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3559235","url":null,"abstract":"","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"18 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143857738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation Information Enhanced Graph Anomaly Detection via Hypergraph Transformation","authors":"Changqin Huang;Chengling Gao;Ming Li;Yongzhi Li;Xizhe Wang;Yunliang Jiang;Xiaodi Huang","doi":"10.1109/TCYB.2025.3558941","DOIUrl":"10.1109/TCYB.2025.3558941","url":null,"abstract":"Graph anomaly detection (GAD) has attracted increasing interest due to its critical role in diverse real-world applications. Graph neural networks (GNNs) offer a promising avenue for GAD, leveraging their exceptional capacity to model complex graph structures and relationships. However, existing GNN-based models encounter challenges in addressing the GAD’s fundamental issue—anomaly camouflage, where anomalies mimic normal instances, leading to indistinguishable features. In this article, we propose a novel approach, termed correlation information enhanced GAD (CIE-GAD). Specifically, drawing on the observation that the distribution of homophilic and heterophilic edges differs between abnormal and normal samples, we construct a hypergraph to learn the co-occurrence relationships among adjacent edges. By enhancing the extraction of sample correlation information, we effectively tackle feature similarity caused by anomaly camouflage, thereby enhancing the performance of GAD. Furthermore, we develop a spectral convolution mechanism based on node-level attention fusion, enabling the capture of multifrequency signals. This module performs adaptive fusion tailored to the unique frequency information requirements of each node, mitigating the local heterophily problem. Extensive experiments on various real-world GAD datasets demonstrate that the proposed CIE-GAD outperforms state-of-the-art methods. Notably, our approach achieves AUC-PR improvements of up to 3.47%, with an average gain of 1.5%, demonstrating its effectiveness in detecting anomalies in graph data.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 6","pages":"2865-2878"},"PeriodicalIF":9.4,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143849808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}