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43rd Chinese control Conference, CCC 2024

作者： Liu, Chang Yuan, Yan Cao, Weihua Hu, Yabin China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Computing offload is a key technology in mobile edge computing (MEC). By offloading tasks to the edge servers, it solves the problem that terminal devices in the edge network cannot handle high computing and time sensitive tasks. However, in multi-user scenarios, the resources of edge servers are very limited, and without good offloading decisions, the performance of MEC systems cannot be guaranteed. In this paper, the computation offloading problem of multi-user MEC system is analyzed and modeled and a batch offloading method is proposed. And in response to the shortcomings of the existing algorithms, a neural network combined with genetic algorithm for offloading decision is proposed. Simulation results show that the proposed algorithm performs better than existing algorithms in terms of time complexity and accuracy. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Computation offloading

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Local Directional Centrality Clustering Based on K-nearest Neighbor Outlier Detection and Shared Neighborhood Strategy 13

Local Directional Centrality Clustering Based on K-nearest N...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Liu, Qing Feng, Zihang Yan, Liping Xia, Yuanqing School of Automation Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing100081 China

ISBN: (纸本)9798350361674

Clustering, as an important prerequisite method in data analysis, can uncover potential information in the data and then proceed to the next step of data analysis and processing. The recently proposed boundary-seeking Clustering algorithm using the local Direction Centrality (CDC) is a very effective method for clustering data with heterogeneous density and weak connectivity. However, it still has some shortcomings. On the one hand, the reachable distance is not enough to comprehensively distinguish weak connection situations, which can easily lead to cross cluster connection errors. On the other hand, K-nearest neighbor search is prone to cross cluster search, leading to misjudgment of boundary points and resulting in connection errors. This paper proposes a local direction centrality clustering algorithm based on K-nearest neighbor outlier detection and shared neighborhood strategy (SODCDC) for sparse and weakly connected data. This algorithm uses a K-nearest neighbor outlier detection strategy to relieve K-nearest neighbor cross cluster search and reduces the probability of boundary point misjudgment. At the same time, it uses a shared neighborhood strategy to further prevent cross cluster connections of weakly connected data. Experiments on some datasets have shown that compared to the original algorithm, the proposed algorithm performs better under the commonly used evaluation metrics. © 2024 IEEE.

关键词： Nearest neighbor search

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Integrated Prediction of Unfavorable Geology in Main Tunnel Considering the Geological Conditions of Parallel Tunnel

Integrated Prediction of Unfavorable Geology in Main Tunnel ...

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2024 China automation Congress, CAC 2024

作者： Zhang, Meng Gan, Chao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

Currently, the advanced geological prediction for the main tunnel from the parallel tunnel often employs parallel deduction of detection conclusions, which faces issues such as a lack of diverse geological exploration information, a lack of analysis of geological structures and poor accuracy. In this paper, an integrated prediction method for unfavorable geology in main tunnel considering the geological conditions of parallel tunnel is proposed, which consists of three stages. In the first stage, based on the forecast mileage range and tunnel excavation conditions, the process is divided into four specific cases. In the second stage, it deduces the geology of the main tunnel along the orientation of rock strata occurrence or joint to parallel tunnel and selects the results of the rock strata occurrence or joint deduction according to the distance of the deduction. In the last stage, it deduces the geological conditions of parallel tunnel face and the integration of geophysical and drilling information for predictive conclusions based on the four specific cases. The proposed method offers higher prediction accuracy for rock mass integrity and surrounding rock grades compared to parallel deduction method. © 2024 IEEE.

关键词： Miocene

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The Multiple Pairwise Markov Chain Model Generalized Labeled Multi-Bernoulli Filter 43

The Multiple Pairwise Markov Chain Model Generalized Labeled...

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43rd Chinese control Conference, CCC 2024

作者： Zhou, Yuqin Yan, Liping Liu, Hanzhao Xia, Yuanqing Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing100081 China

ISBN: (纸本)9789887581581

Addressing the challenge of tracking multiple maneuvering targets with non-independent noise, an improved generalized labeled multi-Bernoulli (GLMB) filter, grounded in jump Markov system (JMS) and pairwise Markov chain (PMC) model, is developed in this paper. The proposed algorithm is composed of two parts. In the first part, the PMC model is introduced into GLMB filter to solve the non-independent noise problem in the tracking process by taking the joint variable containing the target state and the measurement information as a Markov process. In the second part, by modeling the motion process of targets as a system with multiple motion models, JMS is incorporated in the first part to tackle the problem of tracking multiple maneuvering targets with non-independent noise. The effectiveness of the proposed algorithm is demonstrated through simulation experiments. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Markov chains

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Road Underground Target Detection in Ground Penetrating Radar Images Based on YOLO Models

Road Underground Target Detection in Ground Penetrating Rada...

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2023 China automation Congress, CAC 2023

作者： Li, Ting Xue, Wei Yang, Xinya Wu, Dongchang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350303759

Ground penetrating radar (GPR) is extensively employed for subsurface road target detection, offering benefits such as convenience, nondestructive testing, rapid data acquisition, and superior resolution. Despite these advantages, interpreting GPR data often depends on the expertise of professionals, resulting in low detection efficiency and low accuracy. To address these challenges, this study introduces an intelligent detection technique for GPR images, utilizing an enhanced YOLOv5 framework. First, considering the problems of the small amount of GPR image datasets and the unclear characteristics caused by the complex underground media, a Dense-C3 module is built by utilizing the structure of DenseNet to enhance the network's capability for extracting features. Subsequently, a channel and spatial hybrid attention module is introduced into the backbone for feature refinement and improving the efficiency. Finally, the multi-class focal loss function is devised to enhance the precision in cases of imbalanced sample classes. Experimental results show that the proposed model surpasses the original YOLOv5 model and various contemporary advanced models. © 2023 IEEE.

关键词： Efficiency

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Multiple Uncertainty Rejection-Based Power Lifting Adaptive Fixed-Time Tracking control 13

Multiple Uncertainty Rejection-Based Power Lifting Adaptive ...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Liu, Yang Ren, Hongru Hui, Yu Li, Hongyi College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao266061 China School of Automation and Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798350361674

This work investigates an adaptive fixed-time tracking control issue of nonlinear systems with the multiple uncertainty. A practically fixed-time lemma is established, and the singularity problem of fixed-time tracking control is handled by exploiting the power lifting technique. Moreover, a nonlinear fixed-time tracking scheme is proposed under the framework of the backstepping, and a simple design process is presented, which can simultaneously tackle uncertain parameters and disturbances. Finally, the numerical simulation is to explain the effectiveness of the proposed method. © 2024 IEEE.

关键词： Backstepping

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Distributed Power Source Planning Based on Improved Particle Swarm Optimization 3

Distributed Power Source Planning Based on Improved Particle...

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3rd Asia Power and Electrical Technology Conference, APET 2024

作者： Wang, Jiahui Tan, Zhili School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350367690

The multitude of advantages offered by distributed power generation units are recognized as crucial factors in enhancing the security of distribution networks. Ensuring the optimal size and placement of distributed generation (DG) units not only enhances system security but also increases profitability. Haphazard placement of DG units may lead to adverse impacts on the power system, resulting in increased power losses and diminished voltage distribution. Therefore, to ensure the optimal size and placement of DG units, this paper proposes a method to optimize DG scheduling and operation, thereby improving voltage distribution, reducing power losses, and enhancing the overall reliability of the entire grid. To reduce power loss (PL) and improve voltage distribution (VP), an adaptive chaotic particle swarm optimization (ACPSO) algorithm is employed to determine the optimal locations and sizes of DG units. By comparing this algorithm with traditional approaches, its efficacy in enhancing performance can be discerned. © 2024 IEEE.

关键词： Power distribution planning

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Simulation Analysis of Ferromagnetic Resonance of 10kV Electromagnetic Voltage Transformer 6

Simulation Analysis of Ferromagnetic Resonance of 10kV Elect...

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6th International Conference on Power and Energy Applications, ICPEA 2023

作者： Cai, Ning Dai, Dongyun You, Yimin Lin, Zhangzheng Wang, Xu Tu, Yuanting Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control School of Electrical Engineering and Automation Xiamen China

ISBN: (纸本)9798350359053

Electromagnetic voltage transformers are usually used as measurement and protection devices in distribution networks with voltage levels of 10kV. The ferromagnetic resonance caused by the nonlinear characteristics of the excitation inductance of the electromagnetic voltage transformer is a common power system accident in the current power grid. Based on the Maxwell 3D module of ANSOFT software, this paper takes the JDZ10-10C1 voltage transformer as the reference model for modeling and simulation. The simulation results show the magnetic flux change of the voltage transformer core and the waveforms of overvoltage and inrush current when ferromagnetic resonance occurs. The amplitude-frequency characteristics of the excitation current are analyzed by Fourier transform. The simulation process further simulates the inductance change of voltage transformer under different voltage levels, which provides a reference for the selection of voltage transformer in engineering practice and has certain reference significance. © 2023 IEEE.

关键词： Electromagnetic simulation

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification From Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20 000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Design of the EPS Motor automation Test System 8

Design of the EPS Motor Automation Test System

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Zhang, Guoqi He, Yongyi Liu, Xingang School of Mechatronic Engineering and Automation Shanghai University Shanghai China Key Laboratory of Intelligent Manufacturing and Robots Shanghai China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

The rapid global development of electric vehicles has heightened the imperative for exacting performance assessments of Electric Power Steering (EPS) systems, a pivotal subsystem within the automotive domain[13]. This research focuses on the EPS automated testing equipment as the research subject, proposing an automated testing system solution for EPS motors in new energy vehicles based on the testing requirements of the entire vehicle factory. The system is primarily composed of three parts: a testing platform, a control cabinet, and an industrial computer, incorporating both hardware devices and software programs. Its purpose is to conduct motor performance tests specifically tailored for EPS power-assisted motors. The testing system can achieve automated execution, data collection, and data analysis, displaying test results and saving test reports. Experimental findings affirm that the motor testing system demonstrates elevated stability and reliability, contributing significantly to the enhancement of testing efficiency and precision, as substantiated by relevant academic literature. © 2024 SPIE.

关键词： Vehicle performance

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