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Short-Term Hybrid Prognostics of Fuel Cells: A Comparative and Improvement Study

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SSRN

SSRN 2024年

作者： Sheng, Chuang Fu, Jun Zu, YanMin Deng, ZhongHua Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Education Ministry Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China School of Electronic Information Engineering Jingchu University of Technology Jingmen448000 China

Accurately predicting the performance degradation trend of fuel cells helps take measures in advance and prolong the service life of the stack, which led to the creation of a novel hybrid forecasting approach. The first grey model prediction method based on residual exponential smoothing optimization (ES-R-GM) can capture the voltage deterioration trend. The integration of two different ES techniques, specifically the double ES (ES2) and cubic ES (ES3), is explored to investigate their effect on improving the predictive accuracy of the GM model. The second method of the adaptive network fuzzy inference system (ANFIS) can characterize local nonlinear behaviour. The simulated annealing (SA) algorithm is utilized to optimize ANFIS results under different fuzzy rule selection strategies. The outcomes of the two types of prediction methods mentioned above are combined to create a hybrid prediction using the data fusion method and the moving window technique. Different hybrid methods are evaluated under general conditions and further detailed optimization. The proposed hybrid framework is verified by the data obtained from the experimental platform. Moreover, when applied to consistent public datasets, the hybrid approach maintains its robustness and accuracy compared with other prognostic methods. © 2024, The Authors. All rights reserved.

关键词： Simulated annealing

Pattern phase transitions in 3D minimal Vicsek model

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EPL 2021年第5期134卷 50004-50004页

作者： Wu, Yue Li, Jiawei Chen, Duxin Li, Xiang Zhang, Hai-Tao Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Southeast Univ Jiangsu Key Lab Networked Collect Intelligence Sch Math Nanjing 210096 Peoples R China Fudan Univ Sch Informat Sci & Engn Adapt Networks & Control Lab Shanghai 200433 Peoples R China Fudan Univ Sch Informat Sci & Engn Ctr Smart Networks & Syst Shanghai 200433 Peoples R China

A large part of biological collective behaviors involves motional formation patterns like migration, vortex, aggregation, etc., in three-dimensional space, but the phase transition principles among these patterns still remain a dilemma. In this letter, by tweaking the vision range of the particles in a minimal collective motion model, phase transitions are observed among gas-like, crystal-like, and liquid-sphere-like patterns. Significantly, the increase of noise magnitudes will destroy the moving direction synchronization of gas-like and crystal-like phases, but not the liquid-sphere-like phase. By contrast, three sub-phases of migration liquid-sphere, vortex liquid-sphere and aggregation liquid-sphere emerge by slightly increasing noise magnitudes. This study sheds some light onto the forming mechanisms of 3D motional patterns of abundant biological groups. These insights could be expected to enable tuning the collective motional formations of multi-unmanned systems or robots by simply tweaking a few dynamical parameters as well. Copyright (C) 2021 EPLA

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Research and application of Transformer based anomaly detection model: A literature review

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arXiv 2024年

作者： Ma, Mingrui Han, Lansheng Zhou, Chunjie Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China

Transformer, as one of the most advanced neural network models in Natural Language processing (NLP), exhibits diverse applications in the field of anomaly detection. To inspire research on Transformer-based anomaly detection, this review offers a fresh perspective on the concept of anomaly detection. We explore the current challenges of anomaly detection and provide detailed insights into the operating principles of Transformer and its variants in anomaly detection tasks. Additionally, we delineate various application scenarios for Transformer-based anomaly detection models and discuss the datasets and evaluation metrics employed. Furthermore, this review highlights the key challenges in Transformer-based anomaly detection research and conducts a comprehensive analysis of future research trends in this domain. The review includes an extensive compilation of over 100 core references related to Transformer-based anomaly detection. To the best of our knowledge, this is the first comprehensive review that focuses on the research related to Transformer in the context of anomaly detection. We hope that this paper can provide detailed technical information to researchers interested in Transformer-based anomaly detection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

Front-end Replication Dynamic Window (FRDW) for Online Motor imagery Classification

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arXiv 2024年

作者： Chen, Xinru An, Jiayu Wu, Huanyu Li, Siyang Liu, Bin Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China Beijing Fenghuo Wanjia Technology Co. Ltd. Beijing100026 China

Motor imagery (MI) is a classical paradigm in electroencephalogram (EEG) based brain-computer interfaces (BCIs). Online accurate and fast decoding is very important to its successful applications. This paper proposes a simple yet effective front-end replication dynamic window (FRDW) algorithm for this purpose. Dynamic windows enable the classification based on a test EEG trial shorter than those used in training, improving the decision speed;front-end replication fills a short test EEG trial to the length used in training, improving the classification accuracy. Within-subject and cross-subject online MI classification experiments on three public datasets, with three different classifiers and three different data augmentation approaches, demonstrated that FRDW can significantly increase the information transfer rate in MI decoding. Additionally, FR can also be used in training data augmentation. FRDW helped win national champion of the China BCI Competition in 2022. © 2024, CC BY.

关键词： Brain computer interface

Sparse Prior Is Not All You Need: When Differential Directionality Meets Saliency Coherence for Infrared Small Target Detection

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Zhou, Fei Fu, Maixia Qian, Yulei Yang, Jian Dai, Yimian Henan Univ Technol Key Lab Grain Informat Proc & Control Minist Educ Zhengzhou 450001 Peoples R China Henan Univ Technol Henan Key Lab Grain Photoelect Detect & Control Zhengzhou 450001 Peoples R China Henan Univ Technol Coll Informat Sci & Engn Zhengzhou 450001 Peoples R China Nanjing Marine Radar Inst Nanjing 210000 Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci & Engn PCA Lab Key Lab Intelligent Percept & Syst High Dimens Inf Nanjing 210000 Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci & Engn Jiangsu Key Lab Image & Video Understanding Social Nanjing 210000 Peoples R China

The infrared small target detection is crucial for the efficacy of infrared search and tracking systems. Current tensor decomposition methods emphasize representing small targets with sparsity but struggle to separate targets from complex backgrounds due to insufficient use of intrinsic directional information and reduced target visibility during decomposition. To address these challenges, this study introduces a sparse differential directionality prior (SDD) framework. SDD leverages the distinct directional characteristics of targets to differentiate them from the background, applying mixed sparse constraints on the differential directional images and continuity difference matrix of the temporal component, both derived from Tucker decomposition. We further enhance the target detectability with a saliency coherence strategy that intensifies target contrast against the background during hierarchical decomposition. A proximal alternating minimization (PAM)-based algorithm efficiently solves our proposed model. Experimental results on several real-world datasets validate our method's effectiveness, outperforming ten state-of-the-art methods in target detection and clutter suppression. Our code is available at: https://***/GrokCV/SDD.

关键词： Tensors Object detection Clutter Matrix decomposition Sparse matrices Correlation Coherence Vectors Target tracking Sparse approximation Proximal optimization saliency map spatial-temporal regularization target detection tensor decomposition

image denoising algorithm based on noise detection

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2008年第3期21卷 298-302页

作者： Jin, Liang-Hai Li, De-Hua State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to remove and restore the detected noisy pixels and keep the noise-free ones unchanged. Experimental results indicate that the proposed algorithm preserves image details well while removing impulsive noise efficiently, and its filtering performance is significantly superior to the classical median filter and some other typical and recently developed improved median filters.

关键词： Median filters

Hop Count Distribution for Minimum Hop-Count Routing in Finite Ad Hoc Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第7期21卷 5317-5332页

作者： Li, Silan Hu, Xiaoya Jiang, Tao Zhang, Rongqing Yang, Liuqing Hu, Hui Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Sch Cyber Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sixth Generat Mobile Commun 6G Res Ctr Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Tongji Univ Sch Software Engn Shanghai 201804 Peoples R China Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China

Hop count distribution (HCD), generally formulated as a discrete probability distribution of the hop count, constitutes an attractive tool for performance analysis and algorithm design. This paper devotes to deriving an analytical HCD expression for a finite ad hoc network under the minimum hop-count routing protocols. Formulating the node distribution with binomial point process, the network is provided as a bounded area with all nodes randomly and uniformly distributed. Considering an arbitrary pair of source node (SN) and destination node, an innovative and straightforward definition is presented for HCD. In order to derive HCD out, an original mathematical framework, named as the equivalent area replacement method (EARM), is proposed and verified. Under the EARM, HCD is derived by first considering the special case where SN locates at the network center and then extending to the general case where SN is randomly distributed. For each case, the accuracy of our HCD model is evaluated by simulation comparison. Results show that our model matches well with the simulation results over a wide range of parameters. Particularly, the derived HCD outperforms the existing formulations in terms of the Kullback Leibler divergence, especially when SN is randomly distributed.

关键词： Routing Ad hoc networks Graphical models Distribution functions Mathematical models Routing protocols Spread spectrum communication Ad hoc networks hop count distribution minimum hop-count route binomial point process random coverage of multiple circles

Recommendations on Designing Practical Interval Type-2 Fuzzy Systems

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arXiv 2019年

作者： Wu, Dongrui Mendel, Jerry M. Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Ming Hsieh Department of Electrical Engineering University of Southern California Los AngelesCA United States College of Artificial Intelligence Tianjin Normal University Tianjin China

Interval type-2 (IT2) fuzzy systems have become increasingly popular in the last 20 years. They have demonstrated superior performance in many applications. However, the operation of an IT2 fuzzy system is more complex than that of its type-1 counterpart. There are many questions to be answered in designing an IT2 fuzzy system: Should singleton or non-singleton fuzzifier be used? How many membership functions (MFs) should be used for each input? Should Gaussian or piecewise linear MFs be used? Should Mamdani or Takagi-Sugeno-Kang (TSK) inference be used? Should minimum or product t-norm be used? Should type-reduction be used or not? How to optimize the IT2 fuzzy system? These questions may look overwhelming and confusing to IT2 beginners. In this paper we recommend some representative starting choices for an IT2 fuzzy system design, which hopefully will make IT2 fuzzy systems more accessible to IT2 fuzzy system designers. Copyright © 2019, The Authors. All rights reserved.

关键词： Membership functions

Real-time Multi-person Eyeblink Detection in the Wild for Untrimmed Video

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arXiv 2023年

作者： Zeng, Wenzheng Xiao, Yang Wei, Sicheng Gan, Jinfang Zhang, Xintao Cao, Zhiguo Fang, Zhiwen Zhou, Joey Tianyi Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Biomedical Engineering Southern Medical University Guangzhou510515 China Department of Rehabilitation Medicine Zhujiang Hospital Southern Medical University Guangzhou510280 China Singapore Singapore

Real-time eyeblink detection in the wild can widely serve for fatigue detection, face anti-spoofing, emotion analysis, etc. The existing research efforts generally focus on single-person cases towards trimmed video. However, multi-person scenario within untrimmed videos is also important for practical applications, which has not been well concerned yet. To address this, we shed light on this research field for the first time with essential contributions on dataset, theory, and practices. In particular, a large-scale dataset termed MPEblink that involves 686 untrimmed videos with 8748 eyeblink events is proposed under multi-person conditions. The samples are captured from unconstrained films to reveal "in the wild" characteristics. Meanwhile, a real-time multi-person eyeblink detection method is also proposed. Being different from the existing counterparts, our proposition runs in a one-stage spatio-temporal way with end-to-end learning capacity. Specifically, it simultaneously addresses the sub-tasks of face detection, face tracking, and human instance-level eyeblink detection. This paradigm holds 2 main advantages: (1) eyeblink features can be facilitated via the face's global context (e.g., head pose and illumination condition) with joint optimization and interaction, and (2) addressing these sub-tasks in parallel instead of sequential manner can save time remarkably to meet the real-time running requirement. Experiments on MPEblink verify the essential challenges of real-time multi-person eyeblink detection in the wild for untrimmed video. Our method also outperforms existing approaches by large margins and with a high inference speed. Copyright © 2023, The Authors. All rights reserved.

关键词： Face recognition