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An improved estimation of distribution algorithm for multi-compartment electric vehicle routing problem

Journal of Systems Engineering and Electronics 2021年第2期32卷 365-379页

作者： SHEN Yindong PENG Liwen LI Jingpeng Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Division of Computing Science and Mathematics University of StirlingStirling FK94LAUK

The multi-compartment electric vehicle routing problem(EVRP)with soft time window and multiple charging types(MCEVRP-STW&MCT)is studied,in which electric multi-compartment vehicles that are environmentally friendly but need to be recharged in course of transport process,are employed.A mathematical model for this optimization problem is established with the objective of minimizing the function composed of vehicle cost,distribution cost,time window penalty cost and charging service *** solve the problem,an estimation of the distribution algorithm based on Lévy flight(EDA-LF)is proposed to perform a local search at each iteration to prevent the algorithm from falling into local *** results demonstrate that the EDA-LF algorithm can find better solutions and has stronger robustness than the basic EDA *** addition,when comparing with existing algorithms,the result shows that the EDA-LF can often get better solutions in a relatively short time when solving medium and large-scale *** experiments show that using electric multi-compartment vehicles to deliver incompatible products can produce better results than using traditional fuel vehicles.

关键词： multi-compartment vehicle routing problem electric vehicle routing problem(EVRP) soft time window multiple charging type estimation of distribution algorithm(EDA) Lévy flight

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Semantic Maximum Relevance and Modal Alignment for Cross-Modal Retrieval 22

Semantic Maximum Relevance and Modal Alignment for Cross-Mod...

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Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition

作者： Pingping Sun Baohua Qiang Zhiguang Liu Xianyi Yang Guangyong Xi Weigang Liu Ruidong Chen Shihao Zhang Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC China

ISBN: (纸本)9781450397056

With the increasing abundance of multimedia data resources, researches on mining the relationship between different modalities to achieve refined cross-modal retrieval are gradually emerging. In this paper, we propose a novel Semantic Maximum Relevance and Modal Alignment (SMR-MA) for Cross-Modal Retrieval, which utilizes the pre-trained model with abundant image text information to extract the features of each image text, and further promotes the modal information interaction between the same semantic categories through the modal alignment module and the multi-layer perceptron with shared weights. In addition, multi-modal embedding is distributed to the normalized hypersphere, and angular edge penalty is applied between feature embedding and weight in angular space to maximize the classification boundary, thus increasing both intra-class similarity and inter-class difference. Comprehensive analysis experiments on three benchmark datasets demonstrate that the proposed method has superior performance in cross-modal retrieval tasks and is significantly superior to the state-of-the-art cross-modal retrieval methods.

关键词： Semantic Relevance CLIP Cross-Modal Retrieval Modal Alignment

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An Expansion-based Document Ranking Framework Incorporated with Core Concern Capturing 5

An Expansion-based Document Ranking Framework Incorporated w...

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5th International Conference on intelligent Autonomous Systems, ICoIAS 2022

作者： Qi, Yinqiao Xin, Jinghao Li, Ning Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

Entity-based ranking is a popular research area in document ranking as knowledge graphs can introduce additional evidence for ranking systems. In most entity-based ranking framework, the original query is transformed into a set of entities and candidate documents are ranked according to their relevance to the entity set. However, mistakes can easily occur during the transformation process, which introduce noise to the ranking system. This paper represents an expansion-based ranking framework, which expand the original query with high-quality candidate entities to mitigate the impact of transformation mistakes and enrich the semantics of the query in the meanwhile. Compared with existing query expansion methods, our expansion method is lightweight as it reduces much computational burden and requests little extra information. However, the core concerns of the users might be covered up after query expansion. To alleviate this dilemma, a core concern capturing method is pro-posed, wherein the attention weight of each inter-entity relation is measured to capture the core entity pairs in the expanded query. Experiments on the S2-CS dataset demonstrate the effectiveness of our lightweight query expansion method and the superiority of our core concern capturing method. Compared with a classical retrieval model, our method provides 11% improvements in terms of NDCG@15. © 2022 IEEE.

关键词： Semantics

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Object Detection Algorithm Based on Coordinate Attention and Context Feature Enhancement 22

Object Detection Algorithm Based on Coordinate Attention and...

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Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition

作者： Lingzhi Liu Baohua Qiang Yuanchun Wang Xianyi Yang Jubo Tian Shihao Zhang Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC China

ISBN: (纸本)9781450397056

In recent years, object detection has been widely used in various fields such as face detection, remote sensing image detection and pedestrian detection. Due to the complex environment in the actual scene, we need to fully obtain the feature information in the image to improve the accuracy of object detection. This paper proposes an object detection algorithm based on coordinate attention and contextual feature enhancement. We design a multi-scale attention feature pyramid network, which first uses multi-branch atrous convolution to capture multi-scale context information, and then fuses the coordinate attention mechanism to embed location information into channel attention, and finally uses a bidirectional feature pyramid structure to effectively fuse high-level features and low-level features. We also adopt the GIoU loss function to further improve the accuracy of object detection. The experimental results show that the proposed method has certain advantages compared with other detection algorithms in the PASCAL VOC datasets.

关键词： Feature pyramid network Object detection Coordinate attention Atrous convolution

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Kernel-Guided Texture-Aware Blind Super-Resolution via Uncertainty Learning 13

Kernel-Guided Texture-Aware Blind Super-Resolution via Uncer...

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13th International Conference on information Technology in Medicine and Education, ITME 2023

作者： Zhao, Tingting Li, Zuoyong Quan, Li Zeng, Kun Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China College of Computer Science and Big Data Fuzhou University Fuzhou350121 China

ISBN: (纸本)9798350319156

The accuracy of kernel estimation is critical to the performance of blind super-resolution (SR). Traditional kernel estimation methods usually use L1 or L2 loss function to minimize the difference between the estimated kernel and the ground-truth kernel. This tends to make the estimated kernel converge towards the average of all possible kernels, deviating from the ground-truth kernel. To improve the performance of kernel estimation, this paper proposes an uncertainty loss for training a kernel estimation network, focusing on regions with high uncertainty (variance) in the kernel. In addition, a texture-aware SR network is proposed that utilizes the Gumbel Softmax trick to pay more attention to the complex regions of the image texture, thus improving the SR performance. Extensive experiments on synthetic datasets show that our approach achieves promising performance. © 2023 IEEE.

关键词： Textures

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Integrated Power and Hydrogen Trading in Multimicrogrid Coupled with Offsite Hydrogen Refueling Stations 6

Integrated Power and Hydrogen Trading in Multimicrogrid Coup...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Li, Longyan Ning, Chao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350347159

This paper proposes a novel two-level electricity and hydrogen market framework for multi-microgrids (MMGs) coupled with offsite hydrogen refueling stations (HRSs), aiming to strengthen the synergy between electricity and hydrogen. The local hydrogen market among the MMG and HRSs is modeled by multi-leader multi-follower Stackelberg game theory, in which microgrids play the role of leaders to adjust hydrogen prices while HRSs participate as followers to determine their hydrogen purchase scheme. Moreover, to deal with economic and technical issues of the MMG in a holistic manner, Nash bargaining theory is used to model the electricity transaction among microgrids. A distributed algorithm is developed to solve such games, thus reducing the cost of information communication and the risk of privacy exposure. The case study demonstrates that this market mechanism guarantees benefits for all parties and boosts the independence of MMGs by reducing transactions with the main grid. © 2022 IEEE.

关键词： Game theory

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Quantum gyroscopes based on double-mode surface-acoustic-wave cavities

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Physical Review Applied 2024年第1期22卷 014061-014061页

作者： Yuting Zhu Shibei Xue Fangfang Ju Haidong Yuan Department of Automation Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 People’s Republic of China School of Physics and Electronics Department of Mechanical and Automation Engineering

Recent progress shows that a surface-acoustic-wave (SAW) cavity can not only induce quantum acoustic dynamics, but can also form optomechanical-like systems. Its operating frequencies in the microwave band make it resistant to the thermal noise of surrounding environments, while its radiation-pressure couplings make it susceptible to weak forces. Based on these advantages, we propose a gyroscope comprising coupled microwave-SAW cavities. In this paper we systematically consider the range, signal-to-noise ratio, and sensitivity, which are the three most important indices to gyroscopes, but only partially considered in existing works. Additionally, we establish the fundamental limits of sensitivity when the quantum input is in the vacuum state and the squeezed vacuum state. We find that squeezing improves sensitivity and can surpass the standard quantum limit. However, this improvement can only reach up to 2/2 even as the squeezed parameter approaches infinity, which is rarely noted in recent works. Finally, we also offer analytical constraints for cooperativity and squeezed parameters. These constraints can be utilized to design gyroscopes based on coupled cavities in experiments.

关键词： Open quantum systems & decoherence Quantum sensing Rotation sensing Coupled oscillators Cavity resonators Homodyne & heterodyne detection Microwave techniques Surface acoustic wave

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A Foreground Feature Embedding Network for Object Detection in Remote Sensing images 18th

A Foreground Feature Embedding Network for Object Detection...

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18th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2023

作者： Wu, Jiahui Cai, Yuanzheng Wang, Tao Luo, Zhiming Shan, Senhua Li, Zuoyong College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350108 China Department of Artificial Intelligence Xiamen University Xiamen361005 China Istrong Technology Limited Company Fuzhou350108 China

ISBN: (纸本)9789819996360

Compared with traditional natural images, remote sensing images (RSIs) typically have high resolution. The objects in the images are densely distributed, with heterogeneous orientation and large scale variation, even among objects of the same class. In recent years, object detection algorithms have made great strides in general images, but they are still difficult to meet the challenges that exist in RSIs. Therefore, we propose a foreground feature embedding network (FFE-Net) for object detection in RSIs. To better grasp the object features in RSIs, we design a foreground feature embedding module (FFEM) to learn the foreground features of the object. This is achieved by introducing an additional semantic segmentation branch and embedding the features in the classification and regression branches. Simultaneously, we propose a modified Gaussian function with focal loss (MGFFL) as a way to eliminate the extra background noise from soft labels, making the learned foreground features more robust. Our experimental results on two publicly available remote sensing image datasets, DOTA-v1.0 and HRSC2016, validate the effectiveness of FFE-Net. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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Circular Target Attack-Defense Stackelberg Game for Multi-Agents Systems

Circular Target Attack-Defense Stackelberg Game for Multi-Ag...

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第35届中国过程控制会议

作者： Ning Xing Hai-Tao Zhang Yaozhong Zheng School of Artificial Intelligence and Automation Engineering Research Center of Autonomous Intelligent Unmanned Systems Key Laboratory of Image Processing and Intelligent Control State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and Technology

In this paper, the problem of guarding a circular area is proposed and solved using a Stackelberg differential game theoretic approach. The objective of the attacker is to breach the perimeter of the defended area, while the defenders endeavor to thwart such attempts. The dynamics of the attack-defense game are modeled according to the distance and position relations among defenders, attackers, and the center of defense area. The optimal Stackelberg equilibrium control strategies for both defenders and attackers are designed to guarantee the defense mission's success. Then, the effectiveness of the proposed method is validated through numerical simulation.

关键词： Multi-agents system Stackelberg differential game graphical game

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission 24

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Yin, Junpeng Fu, Yusun Huang, Haobo Tang, Jinhui Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China School of Electronic Information and Electrical Engineering The Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme. © 2024 IEEE.

关键词： Audio signal processing

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