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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Zhang, Xin-Kai Li, Ji-Gong Yang, Jing School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin Tianjin China School of Information Technology Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9798350356618

Toxic/hazardous gas leaks seriously jeopardize public safety and the ecological environment, and how to utilize drones with on-board gas sensors to quickly detect gas plumes at an early stage of a gas leak and take timely measures can effectively prevent the expansion of the accident. Traditional plume finding methods have the disadvantages of poor targeting, long search times, and repeated exploration in some areas. In view of this, this paper proposes a method of plume finding with frontier-based planner, where a heuristic function is designed to select optimal observation points and thus plan path to search plume. Here an air-mass path model is constructed to estimate the region that would likely be observed by the UAV at a candidate observation site on the frontier, and the area of the unknown part in the region is considered as the environmental exploration gain. The change in flight direction and the distance traveled by the UAV are used as environmental exploration costs when it will fly from its current pose to the candidate observation site. Simulation results show that the proposed frontier-based exploration method for plume finding has good performance in odor source localization tasks in outdoor environments. © 2024 IEEE.

关键词： Direct air capture

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Multi-objective Optimal Operation of Centralized Battery Swap Charging System with Photovoltaic

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 149-162页

作者： Yuanzheng Li Yihan Cai Tianyang Zhao Yun Liu Jian Wang Lei Wu Yong Zhao School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhanChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore College of Mechatronics and Control Engineering Shenzhen UniversityShenzhenChina Department of Electrical&Computer Engineering Stevens Institute of TechnologyHobokenUSA

Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.

关键词： Multi-objective optimization electric vehicle battery swap charging system scheduling photovoltaic

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A Method for Evaluating the Observation Effectiveness of Microwave Remote Sensing Satellite Constellation 7th

A Method for Evaluating the Observation Effectiveness of ...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhang, Tianyao Zhang, Chi Xiao, Jin Wang, Hong China Academy of Space Technology Beijing100094 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789819733316

Satellites tend to form a constellation for better performance over a region of thousands of kilometers. However, how to set up the configuration of the constellation is still a challenge for an engineer. This article proposes several statistical-based metrics to evaluate the effectiveness of constellations from the perspective of observation applications. Then, this article proposes a software tool to analyze the metrics of constellations over a target area. Furthermore, this article illustrates the proposed method with the help of a 40-satellite case study. Finally, this article concludes the proposed method and discusses future work. This method of evaluation for remote sensing constellations would help the engineer determine the design parameters of the large constellation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Satellites

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Linear Regression-Based Autonomous Intelligent Optimization for Constrained Multiobjective Problems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4620-4634页

作者： Wang, Yan Sun, Xiaoyan Zhang, Yong Gong, Dunwei Hu, Hejuan Zuo, Mingcheng China University of Mining and Technology School of Information and Control Engineering Jiangsu Xuzhou221116 China Qingdao University of Science and Technology College of Automation and Electronic Engineering Shandong Qingdao266061 China China University of Mining and Technology Artificial Intelligence Research Institute Jiangsu Xuzhou221116 China

It is very challenging to autonomously generate algorithms suitable for constrained multiobjective optimization problems due to the diverse performance of existing algorithms. In this article, we propose a linear regression (LR)-based autonomous intelligent optimization method. It first extracts typical features of a constrained multiobjective optimization problem by focused sampling to form a feature vector. Then, a LR model is designed to learn the relationship between optimization problems and intelligent optimization algorithms (IOAs). Finally, the trained model autonomously generates a suitable IOA by inputting the feature vector. The proposed method is applied to six constrained multiobjective benchmark test sets with various characteristics and compared with seven popular optimization algorithms. The experimental results verify the effectiveness of the proposed method. In addition, the proposed method is used to solve the operation optimization problems of an integrated coal mine energy system, and the experimental results show its practicability. © 2020 IEEE.

关键词： Feature extraction

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Named Entity Recognition in Chinese Medical Texts Based on RoBERTa-WWM-IDCNN-CRF 25

Named Entity Recognition in Chinese Medical Texts Based on R...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Tang, Lan Kong, Jie Xu, Liang Xi'an Shiyou University School of Computer Xi'an China Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin China

ISBN: (纸本)9798350366600

Electronic medical records and doctor-patient conversations contain a wealth of useful information, such as disease symptoms, drug names, and cure cycles. Traditional deep learning approaches utilize bidirectional recurrent neural networks to encode text, which cannot effectively capture long-distance dependencies in text. In order to identify medical entity types in various texts more accurately, a named entity recognition approach based on RoBERTa-WWM-IDCNN-CRF is proposed. This approach introduces the RoBERTa-WWM pre-trained model, in order to improve the overall understanding of long Chinese texts for the first time. The model generates semantic representations containing prior knowledge. Then, the generated semantic representations are feed to the IDCNN to extract sentence level characteristics. Finally, the global optimal solution is obtained and the results of the named entity are produced through the CRF. The experiment indicates that the improvement of F1 score, accuracy, and recall of RoBERTa-WWM-IDCNN-CRF model are 7.94%, 4.52% and 10.02% comparing with the classical BiLSTM-CRF model. © 2024 IEEE.

关键词： Convolutional neural networks

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Power System Operation Optimization Method of Combined Renewable Energy with Thermoelectric Units Considering Exergy Efficiency 6

Power System Operation Optimization Method of Combined Renew...

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6th International Conference on Energy Systems and Electrical Power, ICESEP 2024

作者： Shi, Jiakui Zongjie, L. Li, Menghui Xie, Hua Peng, E. Wan, Jie School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China School of Energy Science and Engineering Harbin Institute of Technology Harbin China Guoneng Credit Control Interconnection Technology Co. Ltd Beijing China

ISBN: (纸本)9798350353563

In northern China, the demand for winter heating is substantial, leading to a high proportion of heating loads that reduce the flexibility of the power grid in regulating power generation. The pure condensing unit will enter the normal operation condition of ultra-low load (sometimes even undergoing daily start and stop cycles). The economic consumption method of light, electricity, and heat balance of combined heat and power units is proposed. Based on considering the exergy efficiency, the new energy is transferred to the heat load of the heating network to break the fixed mode of 'fixing electricity by heat, 'reduce the light abandonment rate, and improve the operation economy of the system. It has certain reference significance for promoting the safe and efficient consumption and utilization of local large-scale renewable energy. © 2024 IEEE.

关键词： Cogeneration unit economic operation efficiency renewable energy

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Deep Learning Method for Leakage Location Detection of Pneumatic Systems Based on Infrared Thermal Image Evaluation 24

Deep Learning Method for Leakage Location Detection of Pneum...

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7th International Conference on Software engineering and Information Management, ICSIM 2024

作者： Chang, Jiaqi Shi, Yan Yang, Liman Niu, Yanxia Nie, Yulong Yang, Zhiguo Li, Lei Zhang, Wenchao School of Automation Science and Electrical Engineering Beihang University China Engineering Training Center Beihang University China Guangzhou Industrial Control Environmental Protection Technology Co. Ltd China

ISBN: (纸本)9798400709197

Pneumatic systems are an essential fluid transmission method in the industrial field, which can achieve the transmission and control of power or signals. Leakage in pneumatic systems is challenging to detect and is a highly harmful fault. Most existing leak detection methods use flow or pressure sensors to detect specific leakage amounts, while leak localization is still in the traditional manual detection, which significantly restricts localization efficiency. This article establishes a deep learning framework-based thermal image localization method for pneumatic system leak detection. Infrared images captured in the pneumatic system were collected, and then a deep-learning localization method based on the YOLO framework was established. Then, the recognition accuracy of this method was calculated. The results indicate that the accuracy has reached 99.5% of mAP_0.5 and 86.27% of mAP_0.5:0.95, indicating that this work is a meaningful study that can apply intelligent computing to engineering. © 2024 ACM.

关键词： Object detection

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High-speed train positioning based on a combination of Beidou navigation, inertial navigation and an electronic map

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Science China(Information Sciences) 2023年第7期66卷 237-252页

作者： Hui YANG Shuai-Qiang DONG Chun-Hua XIE School of Electrical and Automation Engineering East China Jiaotong University Key Laboratory of Advanced Control & Optimization of Jiangxi Province East China Jiaotong University State Key Laboratory of Performance Monitoring Protecting of Rail Transit Infrastructure East China Jiaotong University

To date, the studies on the combination positioning of high-speed trains have made great progress, but the positioning accuracy of these methods is relatively low. Map-matching positioning can improve positioning accuracy, but information transmission is time-consuming. Few studies incorporate it into combination positioning. To solve the problem, this paper proposes a high-speed train positioning method based on combining a Beidou navigation system, an inertial navigation system, and an electronic map. First, the combination positioning problem is transformed into a multi-objective optimization problem, which weights the direction similarity and distance error to form a fitness function and converts the railway line and the maximum error range of each positioning system into constraints. Second, an improved differential evolution algorithm is proposed to solve this problem. By referencing the gray wolf algorithm,the differential evolution algorithm updates individuals by varying toward the direction of multiple optimal values. Then, a new combination positioning algorithm for high-speed trains is proposed. In the simulation,the increase in positioning speed and accuracy is analyzed and validated. Compared to the current algorithms, the proposed algorithm performs better. The proposed method has practical value for improving the reliability and safety of train operations.

关键词： electronic map multi-objective optimization differential evolution algorithm Beidou navigation system high-speed train positioning

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Asynchronous Learning-Based Output Feedback Sliding Mode control for Semi-Markov Jump Systems: A Descriptor Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1358-1369页

作者： Zheng Wu Yiyun Zhao Fanbiao Li Tao Yang Yang Shi Weihua Gui School of Automation Central South UniversityChangsha 410083China Power Electronics Machines and Control GroupThe University of NottinghamNottingham NG72RDUK Department of Mechanical Engineering University of VictoriaVictoria BC V8W 3P6Canada IEEE

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning *** with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization *** holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow *** upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution ***,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding ***,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

关键词： Asynchronous switching learning-based control output feedback semi-Markovian jump systems sliding mode con-trol(SMC).

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Optimizing Hydrogen Highway Planning Model Considering Hydrogen Cost and Vehicle Flow Effects

Optimizing Hydrogen Highway Planning Model Considering Hydro...

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2024 IEEE IAS Industrial and Commercial Power System Asia, I and CPS Asia 2024

作者： Zhang, Yan Lv, Yong Wan, Yanming Sun, Yuxin Zhang, Xian Wang, Guibin Liu, Chang China Hydrogen Alliance Research Institute Beijing China Shenzhen University School of Mechanical Electrical and Control Engineering Shenzhen China University of Liverpool Department of Electrical and Electronic Engineering Liverpool United Kingdom School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350352290

In recent years, global governments have been actively advocating for the adoption of hydrogen fuel cell vehicles (HFCVs) as a means to foster a more sustainable future in transportation. However, the widespread integration of these vehicles necessitates robust hydrogenation infrastructure support. This paper presents a novel hydrogen highway optimization planning model tailored for the strategic placement of hydrogen refueling stations (HRSs) along highways. Based on the traditional HRS site selection models, this approach innovatively integrates factors encompassing hydrogen procurement, transportation, and utilization. The model optimizes the location, scale of the HRSs and quantity of hydrogen dispensers within each HRS, utilizing the minimum unit cost of hydrogen as the objective function. To verify the effectiveness, the proposed model is applied in the Beijing-Tianjin-Hebei (BTH) and Chongqing regions, conducting HRS location planning across both demonstration and promotion stages and the specific planning results are obtained. This study offers valuable insights into hydrogen infrastructure planning along highways, serving as a reference for future endeavors in this domain. © 2024 IEEE.

关键词： Hydrogen fuels

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