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5th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2023

作者： Bai, Wentao Gu, Suhang Yan, Chao Zhang, Haoyu Jiang, Chunli Guo, Fan School of Computer Science and Engineering Changshu Institute of Technology Changshu China School of Electrical Engineering and Automation Changshu Institute of Technology Changshu China School of Information Science and Technology Hangzhou Normal University Hangzhou China School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China School of Automation Nanjing Institute of Technology Nanjing China

ISBN: (纸本)9798350393521

In the domain of nonlinear hybrid dynamic system modeling, the effectiveness of switched autoregressive exogenous (SARX) systems may face certain restrictions. To address this issue, this paper presents an enhanced switched system framework. In this framework, all SARX subsystems are replaced with gated recurrent neural networks, aiming to overcome these limitations. Importantly, the proposed switched system does not rely on any prior assumptions about the knowledge of operating modes. Finally, a new identification method is proposed based on the expectation-maximization (EM) algorithm, and its effectiveness is validated through a simulation example. © 2023 IEEE.

关键词： Recurrent neural networks

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Hand-eye Calibration of Industrial Robots with 3D Cameras based on Dual Quaternions

Hand-eye Calibration of Industrial Robots with 3D Cameras ba...

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2022 Chinese automation Congress, CAC 2022

作者： Liu, Yongjie Qian, Kun Zhan, Simin Gong, Yefei Southeast University Colledge of Software Engineering Suzhou China Southeast University School of Automation Nanjing China Changshu Institute of Technology School of Electrical and Automation Engineering Changshu China

ISBN: (纸本)9781665465335

In this paper, a hand-eye calibration method with the 3D depth camera is proposed. A set of 3D cube-shaped calibrators are designed, which facilitates the obtainment of the coordinates of the calibration points of these calibrators. Using the point-to-point correspondence between, a registration method is employed to calculate the pose transformation matrix of the object relative to the camera coordinate system under different camera. Constraint equations are formulated based on the positional transformation matrix, and then the hand-eye relation is solving by using dual quaternions and singular value decomposition. Experimental results show that the proposed method achieves higher accuracy, and the calibration process is more convenient for practical application. © 2022 IEEE.

关键词： Industrial robots

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Weld Seam Segmentation in RGB-D Data using Attention-based Hierarchical Feature Fusion

Weld Seam Segmentation in RGB-D Data using Attention-based H...

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2022 Chinese automation Congress, CAC 2022

作者： Zhan, Simin Qian, Kun Liu, Yongjie Gong, Yefei Southeast University College of Software Engineering Suzhou China Southeast University School of Automation Nanjing China Changshu Institute of Technology School of Electrical and Automation Engineering Changshu China

ISBN: (纸本)9781665465335

Accurate weld detection, segmentation, and positioning based on 3D vision is an important prerequisite for guiding the robots to perform weld milling. It is difficult to accurately segment only by 2D images because multiple welds with different morphological characteristics on the same workpiece may be located in multiple different planes, the lighting conditions sometimes change, and overexposure or underexposure may occur. In response, the method for weld instance segmentation based on the hierarchical feature fusion of RGB-D has been proposed, which can extend the module of RGB-D hierarchical feature fusion based on Mask R-CNN feature pyramid network (FPN). The fusion module introduces channel attention and spatial attention to realize the cross-modality fusion of RGB features and depth features in space. In specific, MaskGIoU Head has been added to the Mask R-CNN model to improve the accuracy of weld seam positioning, and the feature pyramid network (FPN) has been built in Mask Head to improve the boundary quality of the weld segmentation. The method presented in this paper has been proved effective and accurate by the results of the experiment. © 2022 IEEE.

关键词： Welds

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Recursive Broadcasting Approach 33

Recursive Broadcasting Approach

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33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Harutyunyan, Hovhannes A. Hovhannisyan, Narek Concordia University Department of Computer Science and Software Engineering MontrealQCH3G 1M8 Canada Institute for Informatics and Automation Problems NAS RA Yerevan0014 Armenia

ISBN: (纸本)9798331524937

Broadcasting is one of the fundamental information dissemination primitives in interconnection networks, where a message is passed from one node (called originator) to all other nodes in the network. Following the increasing interest in interconnection networks, extensive research was dedicated to broadcasting. Two main research goals of this area are finding inexpensive network structures that maintain efficient broadcasting and finding the broadcast time for well-known and widely used network topologies. In the scope of this study, we will mainly focus on determining the broadcast time and nearoptimal broadcasting schemes in networks. Determination of the broadcast time of any node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few network topologies. There also exist various heuristic and approximation algorithms for different network topologies. In this study, we consider the broadcast time problem on graphs that comprise some recursive structures. We initiate a novel direction to designing broadcasting algorithms on recursively defined graphs. We provide a theoretical foundation for future broadcasting studies, as well as discuss several practical applications of the approach we introduce. © 2025 IEEE.

关键词： Interconnection networks (circuit switching)

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Autonomous sortie scheduling for carrier aircraft fleet under towing mode

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Defence Technology(防务技术) 2025年第1期43卷 1-12页

作者： Zhilong Deng Xuanbo Liu Yuqi Dou Xichao Su Haixu Li Lei Wang Xinwei Wang Department of Engineering Mechanics State Key Laboratory of Structural AnalysisOptimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian116024China School of Mathematical Sciences Dalian University of TechnologyDalian 116024China Naval Aviation University Yantai 264001China China State Shipbuilding Corporation Systems Engineering Research Institute Beijing 100094China Department of Automation School of Information Science and TechnologyTsinghua UniversityBeijing 100084China

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft *** primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch *** this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource ***,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as *** analyzing the constraints in sortie scheduling,a mixed-integer planning model is *** particular,the constraint on preparing spot occupancy is improved to further enhance the sortie *** basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance *** efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is *** solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing *** animation of the simulation results is available at ***/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.

关键词： Carrier aircraft Autonomous sortie scheduling Resource allocation Collision-avoidance Hybrid flow-shop scheduling problem

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An Architecture for Adaptive Machine Learning Models using Adversarial and Transfer Learning

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Procedia CIRP 2023年 120卷 1451-1456页

作者： Simon Kamm Praveen Kumar Nasser Jazdi Michael Weyrich University of Stuttgart – Institute of Industrial Automation and Software Engineering Pfaffenwaldring 47 70550 Stuttgart Germany

Machine Learning and especially deep neural networks are more and more used in industrial applications, because they offer new possibilities to gain knowledge from the available data. The algorithms therefore should work during the lifetime of the industrial system, to which the algorithms are applied for improving the overall performance of the system. However, over the lifetime of an industrial system or application, data sources are likely to change. A sensor may be damaged and delivers faulty values or a new sensor is added to the system. A classical deep neural network will deliver incorrect outputs in case of a faulty sensor or cannot use the additional information coming from a new sensor. In both cases, a retraining with the new input space would be necessary, which requires effort for data collection and training of the network. To address these challenges, this paper proposes an architecture that combines separate approaches, namely the Fast Gradient Sign Method and Transfer Learning. To evaluate the combined architecture, it is applied to a real-world task of failure detection in the Air Pressure System (APS) of an automobile.

关键词： Adaptive Machine Learning Adversarial Learning Transfer Learning Regularization Failure Detection

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Accelerated Lifetime Experiment of Maximum Current Ratio Based on Charge and Discharge Capacity Confinement 8th

Accelerated Lifetime Experiment of Maximum Current Ratio Bas...

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8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023

作者： Wang, Baoji Li, Boyan Wang, Qixuan Dong, Lei Gree Altairnano New Energy INC Zhuhai519000 China School of Automation Beijing Institute of Technology Beijing China Tangshan Research Institute of Technology Tangshan China School of Software Engineering Beijing University of Technology Beijing100124 China

ISBN: (纸本)9789819975891

Lithium-ion batteries will undergo continuous aging during the process of charging and discharging. Charging and discharging cycle conditions for lithium-ion batteries are usually an important method to detect the degree of aging of lithium-ion batteries. However, the general aging cycle lasts for thousands of cycles, which is more time consuming. The charge/discharge capacity of the original condition and the accelerated condition are guaranteed to be the same, and the aging path is essentially the same way. The accelerated life test of lithium-ion battery is realized by the constant current rate accelerated operating condition design and the variable current rate accelerated operating condition design with two different constraints, and the accelerated operating condition with the minimum difference between the battery aging path of the original operating condition before acceleration is obtained by the optimization method. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lithium-ion batteries

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5G Indoor Positioning for Manufacturing using Convolutional Neural Networks

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Procedia CIRP 2023年 120卷 1191-1196页

作者： Hannes Vietz Hamza Ben Haj Ammar Sebastian Baum Nasser Jazdi Michael Weyrich University of Stuttgart Institute of Industrial Automation and Software Engineering Pfaffenwaldring 47 70569 Stuttgart Germany

Current disrupting trends in manufacturing like mobile robot-based intralogistics and digital twins require precise indoor positioning. 5G-based positioning has the potential to be more cost-efficient than other positioning systems due to shared hardware for positioning and communication. But first it has to achieve high positioning accuracy and stability. No positioning technique has yet been established as standard in the industry in combination with 5G because traditional positioning approaches can deliver unstable results when multi-path fading, reflections, or missing line-of-sight effects occur. Identifying promising techniques is still an open research topic. It is established in the literature that deep learning-based approaches can mitigate these effects better than traditional ones by learning unique fingerprints that correspond to precise positions. However, fully-connected neural networks tend to overtrain on these fingerprints which again leads to unstable positioning due to a lack of generalization. This can be explained by the inability of fully connected neural networks to learn structural interrelationships in high dimensional data. This is because their input data is flattened, which means the structure is removed. Convolutional neural networks are being widely used with image data and can learn structural interrelationships. This paper presents a technique that uses convolutional neural networks in combination with a channel-smoothing approach to position mobile robots in the research factory ARENA 2036. The results presented in this paper indicate an indoor positioning accuracy similar to other industrial positioning systems, with improved stability compared to a fully-connected approach.

关键词： indoor positioning mobile robots deep learning 5G intralogistics

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CircRNA-disease inference using deep ensemble model based on triple association

CircRNA-disease inference using deep ensemble model based on...

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2022 Chinese automation Congress, CAC 2022

作者： Fu, Laiyi Du, Hongkai Wang, Ying Peng, Qinke Xi'an Jiaotong University School of Automation Science and Engineering Systems Engineering Institute Xi'an China Xi'an Jiaotong University School of Software Engineering Systems Engineering Institute Xi'an China

ISBN: (纸本)9781665465335

Accumulating evidence indicates more and more circular RNAs (i.e. circRNAs) have played a vital role in regulating gene expression and are related to diseases through different biological procedures. Predicting circRNA-disease associations helps to conjecture possible disease related circRNA and facilitate human disease diagnosis and downstream treatment. Nevertheless, little effort was made to uncover the interaction between various diseases and circRNAs. In our work, human circRNA-disease association network is first generated using known miRNA-circRNA interactions and disease related miRNA (microRNA) information. Then we further integrated this information to compute similarity scores between human diseases and circRNAs. Here, we proposed one deep ensemble model called DeepInteract, which first used two stacked auto-encoders to explore hidden features utilizing similarity information, and adopted a 3-layer neuron network to predict the final association. Our method is capable of capturing more complex non-linear features comparing to other approaches. Our results indicate the proposed method is superior to other previous competitors. Many prediction results have been validated by some biological experiments using our model. © 2022 IEEE.

关键词： Association reactions

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Multi-feature fusion friend recommendation algorithm based on complex network

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International Journal of Information and Communication Technology 2023年第4期23卷 401-423页

作者： Pan, Kan Chen, Hailong Liu, Qian Wang, Jian Pu, Yingming Yin, Chunlin Yang, Zheng Zhao, Na Electric Power Research Institute Yunnan Power Grid Co. Ltd. Kunming650217 China School of Software Yunnan University Kunming650504 China College of Information Engineering and Automation Kunming University of Science and Technology Kunming650504 China

At present, one of the problems of friend recommendation algorithms used in most social networks is that these networks often rely on a single index for recommendation. To solve this problem, multi-feature fusion (MFF) algorithm, a social network friend recommendation algorithm based on complex network theory, is proposed. The recommendation algorithm works by firstly divides the existing social networks into different communities. The importance of nodes in a social network is then calculated through the fusion of nodes’ importance information. Lastly, by integrating node importance information, friend number information and the shortest path information features are comprehensively evaluated, so as to generate final friend recommendation list. Simulation shows that with the increase of network nodes, the MFF algorithm outperforms common friend (CF) algorithm and friend similarity (FS) algorithm over all evaluation indicators including P-value, R-value and F1-value. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Complex networks

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