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2nd International Conference on Information technology and Computer Science, ITCS2010

作者： He, Tao Key Laboratory of Opto-Electronic Technology and Intelligent Control Ministry of Education Lanzhou Jiaotong University LZJTU Lanzhou China

ISBN: (纸本)9780769540740

Interlocking system is the key equipment of railway signaling. New-type all-electronic execution unit (AEEU) for computer interlocking system is introduced. As an example of AEEU, characters and fail-safety of DC switches execution module is discussed in detail. Then some advantages of AEEU are emphasized such as reliable, a little space equipment, powerful function, building a network conveniently, easy to maintain, automatic protection while short circuit happened and so on. At the end part of paper, application on AEEU is introduced briefly. © 2010 IEEE.

关键词： Railroads

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An indoor calibration light source of the transmissometers based on spatial light modulation

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optoelectronics Letters 2022年第2期18卷 65-71页

作者： LIANG Jing ZHANG Guoyu ZHANG Jian XU Da CHONG Wei SUN Jiliang School of Opto-Electronic Engineering Changchun University of Science and TechnologyChangchun 130022China1 Opto-Electronic Measurement and Control Instrumentation Jilin Province Engineering Research CenterChangchun 130022China Key Laboratory of Opto-Electronic Measurement and Optical Information Transmission Technology Ministry of EducationChangchun 130022China Meteorological Observation Center China Meteorological AdministrationBeijing 100081China

Aiming at the problem that the calibration results of the transmissometers cannot be traced to the meteorological optical range(MOR) defined by the World Meteorological Organization(WMO). We designed an indoor calibration light source of the transmissometers based on spatial light modulation, focusing on the design of a non-intersecting CzernyTurner spectroscopic system which achieved a spectral resolution of less than 1 nm in the range from 380 nm to 780 nm. Then, the calibration light source’s spectrum matching model is established and the digital micromirror device(DMD)’s surface illuminance distribution law is simulated and analyzed. Finally, the MOR error of the calibrated light source is inverted. The results show that the simulation spectrum error of the 2 700 K absolute color temperature is below ±7.4% in the wavelength range from 380 nm to 780 nm, and the MOR error meets the requirements of the International Civil Aviation Organization in 40-2 000 m of MOR.

关键词： source light error

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Intelligent resource allocation in mobile blockchain for privacy and security transactions: a deep reinforcement learning based approach

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Science China(Information Sciences) 2021年第6期64卷 172-187页

作者： Zhaolong NING Shouming SUN Xiaojie WANG Lei GUO Guoyin WANG Xinbo GAO Ricky Y.K.KWOK School of Communication and Information Engineering Chongqing University of Posts and Telecommunications School of Software Dalian University of Technology State Key Laboratory of Industrial Control Technology Zhejiang University Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Department of Electrical and Electronic Engineering University of Hong Kong

In order to protect the privacy and data security of mobile devices during the transactions in the industrial Internet of Things(IIoT), we propose a mobile edge computing(MEC)-based mobile blockchain framework by considering the limited bandwidth and computing power of small base stations(SBSs). First,we formulate a joint bandwidth and computing resource allocation problem to maximize the long-term utility of all mobile devices, and take into account the mobility of devices as well as the blockchain throughput. We decompose the formulated problem into two subproblems to decrease the dimension of action space. Then,we propose a deep reinforcement learning additional particle swarm optimization(DRPO) algorithm to solve the two subproblems, in which a particle swarm optimization algorithm is leveraged to avoid the unnecessary search of a deep deterministic policy gradient approach. Simulation results demonstrate the effectiveness of our method from various aspects.

关键词： mobile blockchain deep reinforcement learning mobile edge computing power allocation bandwidth allocation

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Application of cold plasma technologies in fiber/polymer composites

Application of cold plasma technologies in fiber/polymer com...

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International Nano-optoelectronic Workshop, iNOW

作者： Qiang, Li Fang, Guo MOE Key Lab. of Opto-electronic Technology and Intelligence Control Lanzhou Jiaotong University Lanzhou 730070 China Chinese Academy of Sciences

In this paper, the characteristics of cold plasma technologies are introduced briefly. The influence of cold plasma treatments on the adhesion between the fiber and the polymer is described. © 2007 IEEE.

ISBN: (纸本)1424415918

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Asymptotic Trajectory Tracking of Stratospheric Airships Based on RISE controllers Under External Uncertainties

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IEEE Transactions on Aerospace and electronic Systems 2025年

作者： Liu, Can Li, Baoquan Dai, Fengzhi Shi, Wuxi Zhang, Xuebo Tiangong University School of Control Science and Engineering Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin300387 China Tianjin University of Science and Technology College of Electronic Information and Automation Tianjin300222 China Nankai University Institute of Robotics and Automatic Information Systems Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China

For a stratospheric airship under internal and external uncertainties, controller strategies with robust integral sign of the error (RISE) are proposed for asymptotic trajectory tracking control. Specifically, a fully connected neural network (FCNN) is constructed with adaptive weight updating to estimate internal uncertainties of the airship system. Then, a self-tuning RISE controller is designed to track trajectories with compensating external disturbance, which enables gain adjustment in realtime according to system feedback. Based on Lyapunov technique and LaSalle-Yoshizawa corollary extension, system stability is strictly analyzed, and asymptotic convergence performance is obtained for trajectory tracking by the designed controller. Moreover, a RISE controller is designed with fixed gain matrices for the airship based on classic control strategies, and asymptotic tracking is also proved. Finally, numerical simulations are conducted with spiral and hovering control to verify performance of the proposed strategies. © 1965-2011 IEEE.

关键词： Lyapunov methods

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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 Non-Iterative Network Utilization Pricing Mechanism for P2P Energy Trading

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1301-1306页

作者： Yun Liu Yunqiang Gao Yuanzheng Li Jizhong Zhu Hoay Beng Gooi School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhan 430074China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore IEEE

To sustain operation and maintenance of an active distribution network(ADN),a network fee should be charged by the distribution network service provider(DNSP)for facilitating the P2P energy trading *** this end,this paper models the interaction among the DNSP and multiple prosumers as a Stackelberg game,and then develops a non-iterative and decentralized transactive mechanism to simultaneously achieve optimal network utilization pricing and peer-to-peer(P2P)*** results in an ADN with four prosumers connected to a common substation bus validate the effectiveness and efficiency of the proposed scheme.

关键词： Distribution network service provider network fee non-iterative peer-to-peer trading prosumer

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An End-to-end Campus Fire Detection Algorithm Incorporating Priori Features 6

An End-to-end Campus Fire Detection Algorithm Incorporating ...

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6th International Conference on Robotics, Intelligent control and Artificial intelligence, RICAI 2024

作者： Liang, Yu Xie, Xinlin Liu, Xuan Wang, Jie Shanxi Key Laboratory of Advanced Control and Industrial Intelligence Intelligence School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)9798331541699

To address the imbalance in detection speed and accuracy caused by smoke, flame, and background confusion in campus video surveillance scenarios, an end-to-end campus fire detection algorithm incorporating priori features is proposed. First, a feature pyramid fusion module guided by priori features is constructed to cascade the multi-scale feature fusion module. The priori features are individually pre-trained by Convolutional Neural Network (CNN) classification network. The feature complementarity between the two is utilized to improve the feature representation of the detection network. Second, a lightweight set prediction detection head is designed. The head does not require manually designed anchors and post-processing strategies, enabling end-to-end detection while balancing speed and accuracy. Finally, a joint loss function that integrates the losses of categorical and bipartite matching is proposed. Focus on the drawbacks of the slow convergence associated with bipartite matching, both classification information and bipartite bit matching are considered in the detection results. Experimental results on the fire detection dataset demonstrate that the proposed algorithm improved average accuracy by 7.8% while maintaining detection speed, effectively balancing speed and accuracy in fire detection. © 2024 IEEE.

关键词： Convolutional neural networks

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Optical properties of＇ Au-core Pt-shell nanorods studied using FDTD simulations

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Frontiers of physics 2016年第3期11卷 123-131页

作者： Jian-Bo Liu Lin Long Yu-Shi Zhang Yue-Ping_Wang Feng-Shou Liu Wei-Yao Xu Ming-Ji Zong Lei Ma Wen-Qi Liu Hui Zhang JiaoYan Jia-Qi Chen Ying-LuJi Xiao—ChunWu College of Opto-electronic Engineering Zaozhuang University Zaozhuang 277100 China Zaozhuang Municipal Center for Disease Control and Prevention Zaozhuang 277100 China CAS Key Laboratory of Standardization and Measurement for Nanotechnology National Center for Nanoseience and Technology Beijing 100190 China

Au-core/Pt-shell nanorods （Au@Pt NRs） have been prepared by a Au nanorod-mediated growth method, and they exhibit high electromagnetic field enhancements under coupling conditions. Boosted by a long-range effect of the high electromagnetic field generated by the Au core, the electromagnetic field enhancement can be controlled by changing the morphology of the nanostruc- tures. In this study, we report the results on the simulations of the electromagnetic field enhancement using a finite difference time domain （FDTD） method, taking the real shapes of the Au@Pt NRs into account. Due to the ＂hot spot＂ effect, the electromagnetic field can be localized between the Pt nanodots. The electromagnetic field enhancement is found to be rather independent of the Pt con- tent, whereas the local roughness and small sharp features might significantly modify the near-field. As the electromagnetic field enhancement can be tuned by the distribution of Pt nanodots over the Au-core, Au@Pt NRs can find potential applications in related areas.

关键词： gold platinum core-shell nanorod FDTD

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Design of RBF Neural Network Based on Improved Canopy-K-means algorithm 20

Design of RBF Neural Network Based on Improved Canopy-K-mean...

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4th High Performance Computing and Cluster Technologies Conference, HPCCT 2020 and the 3rd International Conference on Big Data and Artificial intelligence, BDAI 2020

作者： Lijie, Jia Wenjing, Li Junfei, Qiao Beijing Key Laboratory of Computational Intelligence and Intelligent System College of Electronic and Control Engineering Beijing University of Technology Beijing China

ISBN: (纸本)9781450375603

To solve the problem that RBF neural network parameters are difficult to determine, an improved Canopy-K-means algorithm is proposed to optimize the RBF neural network. By using the density-based Canopy algorithm to roughly cluster the data, the cluster centers of the K-means algorithm are initialized, meanwhile the number of cluster centers is obtained, and the Canopy-K-means algorithm based on the density of samples (CKD) is used to optimize the RBF neural network. Three experiments, including nonlinear function approximation, classification of UCI website datasets, the effluent ammonia nitrogen (NH4-N) prediction in wastewater treatment process were used to verify the effectiveness of the algorithm. The results showed that CKDRBF network had high classification accuracy, strong approximation ability. © 2020 ACM.

关键词： K-means clustering

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