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A heuristically accelerated multi-agent reinforcement learning algorithm applied to flow line maintenance scheduling

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Journal of Computational Information Systems 2015年第6期11卷 2245-2255页

作者： Wang, Xiao Wang, Hongwei Qi, Chao Wang, Xu School of Safety Engineering Shenyang Aerospace University Shenyang China Institute of Systems Engineering/State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

This paper investigates the maintenance scheduling problem in a flow line system consisting of two series machines with a finite buffer in between. The machines deteriorate with age and have multiple deteriorating quality states represented by multiple decreasing yield levels. The maintenance problem of both machines is modeled as semi-Markov decision processes. A heuristically accelerated multi-agent reinforcement learning algorithm with a feature of incorporating heuristic function for action selection is developed to produce a reasonable maintenance scheduling. A comparison with a Ε-greedy search based exploration algorithm, a simulated annealing search based exploration algorithm, a tabu search based exploration algorithm and a neighborhood search based exploration algorithm in reinforcement learning is presented. The results indicate that the proposed heuristically accelerated multi-agent reinforcement learning algorithm is competitive and has a certain advantage for larger problems. Copyright © 2015 Binary Information Press.

关键词： Tabu search

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Modified lifting algorithm and VLSI architecture for the 9/7 wavelet filters

Modified lifting algorithm and VLSI architecture for the 9/7...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chen-Gyi Xiong Zhi-Rong Gao Jin-Wen Tian Jian Liu The State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute of Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Wuhan University of Science and Engineering Hebei China

ISBN: (纸本)0780384032

A new parallel-based lifting algorithm (PBLA) for the 9/7 filters, exploring the parallelism of arithmetic operations in each lifting step, was proposed in this paper. It shortened significantly the critical path of computation, and resulted in a fast VLSI implementation architecture. In comparison with the conventional lifting algorithm based implementation (CLABI), the latency is reduced by more than half from (4T/sub m/ + 8T/sub a/) to (T/sub m/ + 4T/sub a/), which is competitive to that of convolution based implementation CBI, and can be further reduced to Tm by inserting 3 stages of pipeline. The experimental results demonstrate that the proposed architecture has good performances in both speed and area.

关键词： Very large scale integration Discrete wavelet transforms Filters image coding Delay Parallel processing Arithmetic Convolution Hardware Transform coding

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Analysis of a third-order circuit based on a memristor

Analysis of a third-order circuit based on a memristor

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International Conference on Information Science and Technology (ICIST)

作者： Jian Xiao Yi Shen Zhigang Zeng Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

In this paper, a third-order canonical circuit with a memristor is investigated. Unlike the conventional circuit systems, it has an equilibrium set, whose stability is affected by the initial state of the memristor. T... 详细信息

ISBN: (纸本)9781424494408

关键词： Computer languages Mathematical model

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Nested Saturated control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1163-1174页

作者： Meng Li Zhigang Zeng Wuhan National Laboratory for Optoelectronics Wuhan 430074 School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function,saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.

关键词： method saturation differentiable

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Frequency-specific Alterations of Large-scale Functional Brain Networks in Patients with Alzheimer＇s Disease

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Chinese Medical Journal 2015年第5期128卷 602-609页

作者： Yuan-Yuan Qin Ya-Peng Li Shun Zhang Ying Xiong Lin-Ying Guo Shi-Qi Yang Yi-Hao Yao Wei Li Wen-Zhen Zhu Department of Radiology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei 430074 China

Background：Previous studies have indicated that the cognitive deficits in patients with Alzheimer＇s disease （AD） may be due to topological deteriorations of the brain ***,whether the selection of a specific frequency band could impact the topological properties is still not *** hypothesis is that the topological properties of AD patients are also ***：Resting state functional magnetic resonance imaging data from l0 right-handed moderate AD patients （mean age：64.3 years; mean mini mental state examination [MMSE]：18.0） and 10 age and gender-matched healthy controls （mean age：63.6 years; mean MMSE：28.2） were enrolled in this *** global efficiency,the clustering coefficient （CC）,the characteristic path length （CpL）,and ＂small-world＂ property were calculated in a wide range of thresholds and averaged within each group,at three different frequency bands （0.01-0.06 Hz,0.06-0.11 Hz,and 0.11-0.25 Hz）.Results：At lower-frequency bands （0.01-0.06 Hz,0.06-0.11 Hz）,the global efficiency,the CC and the ＂small-world＂ properties of AD patients decreased compared to *** at higher-frequency bands （0.11-0.25 Hz）,the CpL was much longer,and the ＂small-world＂ property was disrupted in AD,particularly at a higher *** topological properties changed with different frequency bands,suggesting the existence of disrupted global and local functional organization associated with ***：This study demonstrates that the topological alterations of large-scale functional brain networks inAD patients are frequency dependent,thus providing fundamental support for optimal frequency selection in future related research.

关键词： Alzheimer＇s Disease Frequency Network

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Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Counting

arXiv

引用

arXiv 2023年

作者： Wang, Zhicheng Xiao, Liwen Cao, Zhiguo Lu, Hao 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

Class-agnostic counting (CAC) aims to count objects of interest from a query image given few exemplars. This task is typically addressed by extracting the features of query image and exemplars respectively and then matching their feature similarity, leading to an extract-then-match paradigm. In this work, we show that CAC can be simplified in an extract- and-match manner, particularly using a vision transformer (ViT) where feature extraction and similarity matching are executed simultaneously within the self-attention. We reveal the rationale of such simplification from a decoupled view of the self-attention. The resulting model, termed CACViT, simplifies the CAC pipeline into a single pretrained plain ViT. Further, to compensate the loss of the scale and the order-of-magnitude information due to resizing and normalization in plain ViT, we present two effective strategies for scale and magnitude embedding. Extensive experiments on the FSC147 and the CARPK datasets show that CACViT significantly outperforms state-of-the-art CAC approaches in both effectiveness (23.60% error reduction) and generalization, which suggests CACViT provides a concise and strong baseline for CAC. Code will be available. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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MBGD-RDA Training and Rule Pruning for Concise TSK Fuzzy Regression Models

arXiv

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arXiv 2020年

作者： Wu, Dongrui 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

To effectively train Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a Mini-Batch Gradient Descent with Regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. It has demonstrated superior performances;however, there are also some limitations, e.g., it does not allow the user to specify the number of rules directly, and only Gaussian MFs can be used. This paper proposes two variants of MBGD-RDA to remedy these limitations, and show that they outperform the original MBGD-RDA and the classical ANFIS algorithms with the same number of rules. Furthermore, we also propose a rule pruning algorithm for TSK fuzzy systems, which can reduce the number of rules without significantly sacrificing the regression performance. Experiments showed that the rules obtained from pruning are generally better than training them from scratch directly, especially when Gaussian MFs are used. Copyright © 2020, The Authors. All rights reserved.

关键词： Gradient methods

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Defocus to focus: photo-realistic bokeh rendering by fusing defocus and radiance priors

arXiv

引用

arXiv 2023年

作者： Luo, Xianrui Peng, Juewen Xian, Ke Wu, Zijin Cao, Zhiguo 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

We consider the problem of realistic bokeh rendering from a single all-in-focus image. Bokeh rendering mimics aesthetic shallow depth-of-field (DoF) in professional photography, but these visual effects generated by existing methods suffer from simple flat background blur and blurred in-focus regions, giving rise to unrealistic rendered results. In this work, we argue that realistic bokeh rendering should i) model depth relations and distinguish in-focus regions, ii) sustain sharp in-focus regions, and iii) render physically accurate Circle of Confusion (CoC). To this end, we present a Defocus to Focus (D2F) framework to learn realistic bokeh rendering by fusing defocus priors with the all-in-focus image and by implementing radiance priors in layered fusion. Since no depth map is provided, we introduce defocus hallucination to integrate depth by learning to focus. The predicted defocus map implies the blur amount of bokeh and is used to guide weighted layered rendering. In layered rendering, we fuse images blurred by different kernels based on the defocus map. To increase the reality of the bokeh, we adopt radiance virtualization to simulate scene radiance. The scene radiance used in weighted layered rendering reassigns weights in the soft disk kernel to produce the CoC. To ensure the sharpness of in-focus regions, we propose to fuse upsampled bokeh images and original images. We predict the initial fusion mask from our defocus map and refine the mask with a deep network. We evaluate our model on a large-scale bokeh dataset. Extensive experiments show that our approach is capable of rendering visually pleasing bokeh effects in complex scenes. In particular, our solution receives the runner-up award in the AIM 2020 Rendering Realistic Bokeh Challenge. © 2023, CC BY-NC-ND.

关键词： image fusion

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Fault Diagnosis of SOFC Stack Based on Neural Network Algorithm

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Energy Procedia 2019年 158卷 1798-1803页

作者： Tao Xue Xiaolong Wu Yuanwu Xu Suwen Jing Zehua Li Jianhua Jiang Zhonghua Deng Xiaowei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China

To realize the commercialization of SOFC, it must be ensured that it can work efficiently and stably. SOFC fault diagnosis becomes an essential part of the research. Due to the strong coupling of faults in the stack, this paper uses neural network algorithm to detect and diagnose faults. The simulation results verify that through the diagnosis of the test sample, the recognition rate of the test sample by the network is found to be 95%, which explains the neural network fault diagnosis model established in this paper on identifying the normal working state of the stack, the electrode stacking of the stack, and the gas leakage fault of the stack has good effectiveness and accuracy.

关键词： SOFC fault diagnosis neural network

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Parametric Design Optimization of a Universal Supernumerary Robotic Limb

Parametric Design Optimization of a Universal Supernumerary ...

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International Symposium on Micromechatronics and Human Science (MHS)

作者： Jun Huo Bo Yang Hongge Ru Jian Huang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology (HUST) Wuhan China

ISBN: (纸本)9781665407748

It is a positive trend for hemiplegia with wearable robots in rehabilitation training. Recently, wearable Supernumerary Robotic Limb (SRL) is rising to a hot spot. The difficulty in modeling SRL for hemiplegia is how to make the SRL mechanism match the human upper and lower limbs' size and function simultaneously. In this paper, a simplified model of a four Degree of Freedoms (DOFs) universal SRL (USRL) is introduced. Based on workspace similarity, which is evaluated by Jaccard Index (JI), we establish a multi-object optimization (MOO) model. By applying the Particle Swarm Optimization (PSO) algorithm, we have found the optimal SRL mechanism parameters that meet the requirement of the human upper limb and the cane simultaneously. Meanwhile, a few impact factors are discussed briefly in the present proposal. The simulation results show that the USRL has a sound match with the human and could assist the hemiplegia subject as a supplemental limb.

关键词： Training Simulation Wearable robots Market research Manufacturing Indexes Proposals

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