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A large-scale group SLIM considering expert credibility under social network to estimate human error probabilities in the railway driving process

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 255卷

作者： Zhou, Jian-Lan Zhou, Ya-Lun Xiao, Ren-Bin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci Technol Res Inst Shenzhen 518057 Peoples R China

The Large-scale Group Success Likelihood Index Method (LG-SLIM) can eliminate bias caused by a single expert in human error assessment. The traditional LG-SLIM uses trust degrees to cluster and reach a consensus. However, the existing clustering algorithms do not consider the trust degrees between a given pair of experts to be multiple and vary according to different evaluated tasks. Besides, the existing consensus models do not consider various combinations of the evaluated tasks and trusted experts' professions when managing trust degrees and self-confidence. Therefore, the similarity-trust-based clustering algorithm is improved using the comprehensive trust degree integrated from diverse trust degrees concerning all evaluated tasks. Moreover, expert credibility is proposed to reflect the quality of the expert's evaluation results, determined by self-confidence and trust degree simultaneously according to various combinations of the expert profession and target task. Accordingly, under the social network derived from expert credibility, the incompatible outliers change their opinions by referring to the views of those with the highest expert credibility. Finally, the sensitivity experiment and comparative analysis verify the effectiveness of the proposed model. The proposed LG-SLIM model is useful for human error assessment when critical operations need many experts to obtain reliable and accurate results.

关键词： Railway operation Success likelihood index method Human error analysis Expert credibility Social network Large-scale group decision-making

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Statistical Feasibility Robust Optimization With Polyhedron Uncertainty Set for Hydrogen-Data Center Microgrid Operations

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 9884-9902页

作者： Duan, Juntao Li, Yuanzheng Li, Yang Yang, Pu Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Northeast Elect Power Univ Sch Elect Engn Jilin 132000 Peoples R China Tencent Technol Shenzhen Co Ltd Shenzhen 518057 Guangdong Peoples R China

Robust optimization (RO) has been widely used in the hydrogen-data-center microgrid (H-2- DCMG) optimal operations. However, the operation results based on RO are too conservative. Statistical feasibility can be introduced into RO to reduce conservatism. Therefore, statistical feasibility-based RO is adopted in the H-2- DCMG operations optimization. In this study, a data-driven statistical-feasibility-based robust rolling optimization framework is constructed for the optimal operations of the c-DCMG. In this framework, DC temperature is influenced by the uncertain outside temperature, and an uncertainty set is needed to express the uncertain outside temperature. Unfortunately, the existing studies that construct the uncertainty set satisfying statistical feasibility only constructs the ellipsoid uncertainty sets. The ellipsoid uncertainty sets will be converted into the second-order cone constraints, which will increase the complexity when solving. In this study, the Statistical-Guarantee-based Vertex Link (SGVL) algorithm is proposed to construct the polyhedron uncertainty sets, which are used to describe the uncertainty of the outside temperature. Moreover, statistical feasibility-based DC temperature bound is guaranteed by the optimal operations obtained based on these uncertainty sets. Compared with the traditional ellipsoid uncertainty set, the polyhedron uncertainty set can reduce the complexity of the optimization problem and improve the efficiency of the solution process. Case studies based on the real-world temperature dataset are processed. The results show that the introduction of statistical feasibility can reduce the total operation cost by 0.29%similar to 0.64%. The average solving time of the optimization problems based on the polyhedron uncertainty sets constructed using the SGVL algorithm also reduces by 7%similar to 13%. The cases also verify that other uncertainty parameters and different kinds of forecasters do not influence the performance and e

关键词： Uncertainty Optimization Temperature distribution Upper bound Servers Microgrids Heating systems Data centers Hydrogen Greenhouse gases Hydrogen energy storage system data center microgrid statistical feasibility robust optimization

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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A CSP-based retraining framework for motor imagery based brain-computer interfaces

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Science China(Information Sciences) 2024年第8期67卷 349-350页

作者： Xue JIANG Lubin MENG Xinru CHEN Dongrui WU Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

Motor imagery(MI) is a classic paradigm of electroencephalogram(EEG)-based brain-computer interfaces(BCIs). It entails individuals mentally imagining the movement of a body part without physically performing it. EEG s... 详细信息

关键词： Classification (of information)

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An Evaluation Method of Dental Treatment Quality Combined with Deep Learning and Multi-index Decomposition

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APPLIED ARTIFICIAL INTELLIGENCE 2024年第1期38卷

作者： Peng, Gang Liu, Jie Yan, Feng Liu, Beicun Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat 1037 Luoyu Rd Wuhan Hubei Peoples R China Minist Educ Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Hubei Eya Med Investment Management Co Ltd Res Ctr Wuhan Peoples R China

Dentists judge that the quality of dental treatment for each patient is very time-consuming and inefficient, lacks quantitative evaluation criteria, and is easy to cause errors. At the same time, the traditional method of extracting tooth and root canal image features based on experience is difficult to accurately extract the tooth area and root canal filling area, resulting in low accuracy of tooth and root canal segmentation, which in turn affects the accuracy of tooth treatment quality evaluation. In this paper, a deep learning convolutional neural network is used to segment the root canal filling area, tooth boundary, and the boundary between tooth and soft tissue for the real patient 's root canal treatment and filling image. Finally, the segmented image is quantitatively evaluated according to the multi-evaluation index of professional doctors. The experimental results show that the intelligent evaluation method of dental treatment quality combined with deep learning and multi-index decomposition proposed in this paper not only unifies the evaluation criteria of dental treatment quality but also the therapeutic effect of quantitative scoring can effectively improve the work efficiency of doctors, which has reference significance for the application of artificial intelligence in the medical field.

关键词： Deep learning

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controllability of Cartesian Product Signed Networks

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第11期53卷 7125-7137页

作者： Liu, Bo Hu, Mengjie Huang, Junjie Su, Housheng Minzu Univ China Sch Informat Engn Key Lab Ethn Language Intelligent Anal & Secur Gov Beijing 100081 Peoples R China Inner Mongolia Univ Sch Math Sci Hohhot 010021 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Peoples R China

A necessary and sufficient algebraic condition is obtained for the controllability of a composite signed network consisting of two factor networks by Cartesian product, which reveals how the controllability of the higher-dimensional Cartesian product network is affected by the controllability of its smaller-scale low-dimensional factor networks. Furthermore, the structural balance of the Cartesian product network can be judged by the structural balance of its factor networks, which can greatly reduce amount of calculation to some extent. And the agents' state evolution trajectories of Cartesian product networks can also be predicted by those of their factor networks. Moreover, the controllability of general signed networks is considered. Algorithms and numerical examples are exhibited to demonstrate the validity of our methods.

关键词： Cartesian product signed networks controllability multiagent systems

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Natural Grasp Intention Recognition Based on Gaze in Human-Robot Interaction

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2023年第4期27卷 2059-2070页

作者： Yang, Bo Huang, Jian Chen, Xinxing Li, Xiaolong Hasegawa, Yasuhisa Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Shenzhen Key Lab Biomimet Robot & Intelligent Syst Shenzhen 518055 Peoples R China Rehabil Robot Univ Southern Univ Sci & Technol Guangdong Prov Key Lab Human Augmentat Shenzhen 518055 Peoples R China Nagoya Univ Dept Micronano Mech Sci & Engn Furo cho Chikusa ku Nagoya 4648603 Japan

Objective: While neuroscience research has established a link between vision and intention, studies on gaze data features for intention recognition are absent. The majority of existing gaze-based intention recognition approaches are based on deliberate long-term fixation and suffer from insufficient accuracy. In order to address the lack of features and insufficient accuracy in previous studies, the primary objective of this study is to suppress noise from human gaze data and extract useful features for recognizing grasp intention. Methods: We conduct gaze movement evaluation experiments to investigate the characteristics of gaze motion. The target-attracted gaze movement model (TAGMM) is proposed as a quantitative description of gaze movement based on the findings. A Kalman filter (KF) is used to reduce the noise in the gaze data based on TAGMM. We conduct gaze-based natural grasp intention recognition evaluation experiments to collect the subject's gaze data. Four types of features describing gaze point dispersion (f(var)), gaze point movement (f(gm)), head movement (f(hm)), and distance from the gaze points to objects (f(dj)) are then proposed to recognize the subject's grasp intentions. With the proposed features, we perform intention recognition experiments, employing various classifiers, and the results are compared with different methods. Results: The statistical analysis reveals that the proposed features differ significantly across intentions, offering the possibility of employing these features to recognize grasp intentions. We demonstrated the intention recognition performance utilizing the TAGMM and the proposed features in within-subject and cross-subject experiments. The results indicate that the proposed method can recognize the intention with accuracy improvements of 44.26% (within-subject) and 30.67% (cross-subject) over the fixation-based method. The proposed method also consumes less time (34.87 ms) to recognize the intention than the fixation-bas

关键词： Grasp intention recognition gaze movement modeling human-robot interaction feature extraction

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Predefined-Time Synchronization of Multiple Fuzzy Recurrent Neural Networks via a New Scaling Function

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第3期32卷 1527-1538页

作者： Liu, Peng Liu, Ting Sun, Junwei Zeng, Zhigang Zhengzhou Univ Light Ind Coll Elect & Informat Engn Zhengzhou 450002 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

This article investigates the predefined-time synchronization of a group of fuzzy recurrent neural networks (FRNNs) under a leaderless communication topology. An effective control strategy is proposed based on a time-dependent exponential function as the scaling function. Sufficient criteria for guaranteeing the predefined-time synchronization of multiple FRNNs are derived under the digraph with strong connectivity and the digraph containing spanning trees, respectively. Unlike commonly used state-dependent sign function or time-dependent power function in existing works, the scaling function in this article is new and selected as the time-dependent exponential function. Moreover, the communication topology in this article is assumed to be leaderless, which is distinct from the master-slave or leader-following topologies previously investigated for predefined-time synchronization. Numerical examples are provided to illustrate the correctness of results.

关键词： Synchronization Topology Recurrent neural networks Manganese Behavioral sciences Delays Convergence Fuzzy recurrent neural networks (FRNNs) leaderless topology predefined-time synchronization

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Fog images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network 42

Fog Images Generation About Unmanned Surface Vessels with Im...

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42nd Chinese control Conference, CCC 2023

作者： Tang, Yifeng Huang, Zhihui Tang, Chuancong Luo, Chuanshang Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Generative adversarial networks

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Research on emergence mechanism of collective intelligence from the complexity perspective

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2023年第1期22卷 28-+页

作者： Xiao, Renbin Feng, Zhenhui Wu, Bowen Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

This paper explores the emergence mechanism of collective intelligence (CI) from the complexity perspective. It begins with a comparison of the main features based on the two basic stages of CI, i.e., CI 1.0 (swarm intelligence) and CI 2.0 (crowd intelligence). Considering the connection mechanism between the two stages is still unclear, we would regard higher organism group behaviours as the transition between lower organism group behaviours to crowd behaviours. Accordingly, the bionic prototypes of CI can be classified into three categories: lower organisms, higher organisms and humans. This paper first refined the emergence mechanisms of CI in lower organisms represented by labour division, i.e., stimulus-response mechanism and activation-inhibition mechanism. Subsequently, the higher organism emergence mechanism was revealed, which is the attraction-repulsion mechanism based on roles division and perception driven. Furthermore, the emergence mechanism of crowd intelligence at the perceptual level and cognitive level are presented respectively, by means of process evolutionary description based on the attraction-repulsion mechanism. Finally, the research gives a holistic illustration of the emergence mechanism of CI.

关键词： collective intelligence emergence complexity stimulus-response activation-inhibition attraction-repulsion perceptual level cognitive level

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