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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Qi, Jianzhong Song, Qingping School of Information Science and Technology North China University of Technology Beijing100144 China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Science and Technology on Information Systems Engineering Laboratory Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789811580857

In this paper, a method of ranging high-speed aircraft by using the burst DSSS communication pulse is analyzed. In this algorithm, noncoherent PN code is used for ranging and coherent forwarding is used for carrier. In order to eliminate the error caused by the rapid movement of the aircraft, the relative velocity between the objects is measured and the ranging error is corrected. How to estimate the carrier frequency and pseudo code phase in the burst short pulse spread spectrum communication is discussed. Firstly, PMF + FFT is used to capture the signal and estimate the initial value of carrier frequency and pseudo code phase, then LM algorithm is used to solve the maximum likelihood function, so as to obtain the accurate value of carrier frequency and pseudo code delay. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Spectroscopy

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Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

arXiv

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arXiv 2023年

作者： Chen, Xianhao Deng, Yiqin Ding, Haichuan Qu, Guanqiao Zhang, Haixia Li, Pan Fang, Yuguang The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The School of Control Science and Engineering The Shandong Key Laboratory of Wireless Communication Technologies Shandong University Shandong Jinan250061 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The Department of Electrical Engineering and Computer Science Case Western Reserve University ClevelandOH44106 United States The Department of Computer Science City University of Hong Kong Kowloon Hong Kong

Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected and autonomous driving, smart and connected health, and smart living. At the same time, it is widely recognized that vehicles such as autonomous cars, equipped with significantly powerful SCCSI capabilities, will become ubiquitous in future smart cities. By observing the convergence of these two trends, this article advocates the use of vehicles to build a cost-effective service network, called the Vehicle as a Service (VaaS) paradigm, where vehicles empowered with SCCSI capability form a web of mobile servers and communicators to provide SCCSI services in smart cities. Towards this direction, we first examine the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, we will introduce the system architecture of the VaaS paradigm and discuss how it can provide SCCSI services in future smart cities, respectively. At last, we identify the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy. We expect that this paper paves the way towards developing a cost-effective and sustainable approach for building smart cities. Copyright © 2023, The Authors. All rights reserved.

关键词： Edge computing

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A Reinforcement Learning-Based Energy Management Strategy for Fuel Cell Electric Vehicle Considering Coupled-Energy Sources Degradations

SSRN

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SSRN 2022年

作者： Huo, Weiwei Liu, Teng Li, Fajia Institute of Electromechanical Engineering Beijing Information Science & Technology University Beijing100192 China Collaborative Innovation Center of Electric Vehicles in Beijing Beijing Information Science & Technology University Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China University of Jinan Jinan250024 China

The energy management strategy (EMS) is crucial for fuel cell electric vehicles (FCEV) by decreasing the equivalent fuel consumption and postponing fuel cell deterioration. An improved EMS based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) deep reinforcement learning considering energy sources degradation and economic factor is proposed in this paper. The working condition identification (WCI) implemented by ensemble bagged trees (EBT) is used to expand the diversity of EMS application scenarios . The drastic loading change of fuel cell is avoided for minimizing the instantaneous cost (MIC), which reduces fuel cell degradation greatly. TD3 is applied to optimize the total cost combined with WCI and MIC. The training results based on 13 classic working conditions show that the degradation of the fuel cell system is effectively suppressed, decreasing the overall cost and accelerating the algorithm's convergence time significantly. © 2022, The Authors. All rights reserved.

关键词： Energy management

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Performance Enhancement of Nanogenerator by Piezoelectric Filler Microstructure Design Towards Electrical Transmission Power Line Monitoring

SSRN

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SSRN 2025年

作者： Lu, Haowei Hu, Zhenghua Wang, Xin Chen, Gaoru Zheng, Xiaogan Xia, Jintao Huang, Mingju Yang, Wenlong Liu, Junhui Hu, Benlin Henan Key Laboratory of High Efficiency Energy Conversion Science and Technology Henan International Joint Laboratory of New Energy Materials and Devices School of Physics and Electronics Henan University Kaifeng475004 China School of Information and Artificial Intelligence Anhui Agricultural University Hefei230036 China School of Intelligent Manufacturing Wenzhou Polytechnic Wenzhou325035 China State Grid Fuzhou Electric Power Supply Company Fuzhou350009 China School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China CAS Key Laboratory of Magnetic Materials and Devices Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China

Flexible composites-based piezoelectric nanogenerator (PENG) with low cost, stable properties and sensitivity to mechanical deformation is highly suitable for constructing a new self-powered perception layer in distributed electrical transmission power lines, which has the potential to reduce labor maintenance costs and improve sensing recognition accuracy. However, the lower output performance of PENG makes it difficult to integrate with energy management circuit and signal recognition system. Herein, we propose a enhanced output performance of composites-based PENG by designing piezoelectric fillers, where BCZT@Ag nanoparticles grow on the surface of BCZT fibers to form a Bracnch heterostructure. The PENG prepared by this new filler exhibits significantly enhanced output of 96.4 V and 15.52 µA, which are about 3.2 and 6.5 times higher than those of PENG without specific design, benefiting from improved charge transport mechanism and induced-polarization. Moreover, a intelligent Power IoTs system through the synergistic integration of this high-performance PENG and learning-assisted data analytics has been constructed, which enables accurate self-powered real-time monitoring of abnormal vibration states in transmission power lines to avoid rupture accident. This work not only provides an effective strategy to enhance the performance of PENG but also offers a new solution for the safe operation in power grid. © 2025, The Authors. All rights reserved.

关键词： Piezoelectricity

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Q estimation using multifrequency point average method based on the Taylor series expansion with a different order

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Applied Geophysics 2021年第4期18卷 557-568,595页

作者： Zhang Jin Wang Yan-Guo Zhang Guo-Shu Lan Hui-Tian Zhang-Hua Hao Ya-Ju College of Geophysics and Measurement-control East China University of TechnologyNanchang 330013China State Key Laboratory of Nuclear Resources and Environment East China University of TechnologyNanchang 330013China College of Nuclear Science and Engineering East China University of TechnologyNanchang330013China Exploration and Development Research Institute of Daqing Oil Company Daqing 163712China.

The quality factor Q is an important parameter because it can refl ect the reservoir attenuated features and can be used for inverse-Q filtering to compensate for the seismic wave *** accuracy of the Q estimation is greatly significant for improving the precision of the reservoir prediction and the resolution of seismic *** this paper,the Q estimation formulas of the single-frequency point are derived on the basis of a diff erent-order Taylor series expansion of the amplitude attenuated ***,the multifrequency point average(MFPA)method is introduced to obtain a stable Q *** model tests demonstrate that the MFPA method is less aff ected by the frequency band,travel time diff erence,time window width,and noise interference than the logical spectrum ratio(LSR)method and the energy ratio(ER)method and has a higher Q estimation *** addition,the proposed method can be applied to post-stack seismic data and obtain eff ective Q values of complex *** the MFPA method was applied to real marine seismic data,the Q values estimated by the MFPA method with the 1st–4th order showed good consistency with each *** contrast,the Q values obtained by the ER method were larger than those of the proposed method,while those estimated by the LSR method signifi cantly deviated from the average *** conclusion,the MFPA method has superior stability and practicability for the Q estimation.

关键词： Q estimation Taylor series expansion Precision Stability

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Sparse optimization of mutual synchronization in collectively oscillating networks

arXiv

引用

arXiv 2021年

作者： Nakao, Hiroya Yamaguchi, Katsunori Katayama, Shingo Yanagita, Tatsuo Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Department of Engineering Science Osaka Electro-Communication University Neyagawa Osaka572-8530 Japan

We consider a pair of collectively oscillating networks of dynamical elements and optimize their internetwork coupling for efficient mutual synchronization based on the phase reduction theory developed in Ref. [H. Nakao, S. Yasui, M. Ota, K. Arai, and Y. Kawamura, Chaos 28, 045103 (2018)]. The dynamical equations describing a pair of weakly coupled networks are reduced to a pair of coupled phase equations, and the linear stability of the synchronized state between the networks is represented as a function of the internetwork coupling matrix. We seek the optimal coupling by minimizing the Frobenius and L1norms of the internetwork coupling matrix for the prescribed linear stability of the synchronized state. Depending on the norm, either a dense or sparse internetwork coupling yielding efficient mutual synchronization of the networks is obtained. In particular, a sparse yet resilient internetwork coupling is obtained by L1-norm optimization with additional constraints on the individual connection weights. Copyright © 2021, The Authors. All rights reserved.

关键词： Synchronization

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Analysis and Study on Grid-Connected Photovoltaic Solar Power Plant using Artificial Intelligence

Analysis and Study on Grid-Connected Photovoltaic Solar Powe...

引用

Innovation in technology (APCIT), Asia Pacific Conference on

作者： Devendra Sood Sumit Kumar Pawan Agarwal Akhilesh Singh Abhishek Chakravorty Shweta Goyal Deptt. of CSE Tula’s Institute Dehradun India Dept of Mechanical Engineering JB Instiitute of Technology Dehradun Uttarakhand Deptt. of Professional Communication Graphic Era Hill University Bhimtal Uttarakhand Deptt. of Electrical Engg. Uttarakhand Technical University NPSEI Pithoragarh Campus Deptt. of Instrumentation & Control Tula’s Institute Dehradun India Deptt. of Electrical Engg. Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

The photovoltaic (PV) industry is adopting artificial intelligence (AI) more frequently as a result of advancements in data collecting, tools, and processing power. It has been demonstrated that the current methods employed in many solar photovoltaic sector activities related to design, estimation, management, and monitoring yield positive outcomes; however, complex equipment is needed for the analysis and estimation of the operation and management of the solar photovoltaic power plant. Promoting solar photovoltaic energy is necessary to address climate change-related issues and increase the usage of renewable energy sources. This project's objectives are to assess the efficiency of artificial intelligence (AI) in resolving energy-related issues and investigate the effects of grid-connected photovoltaic (PV) systems. Research has been done on the effects of artificial intelligence (AI) on specific PV grid functions. The purpose of this project is to assess the state of artificial intelligence technology at the moment and look at how artificial intelligence may be used in the future.

关键词： Photovoltaic systems Temperature distribution Technological innovation Renewable energy sources Wind speed Estimation Predictive models

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Microstructure and Properties of Graphene Reinforced Co-Based Composite Coating by Laser Cladding

SSRN

引用

SSRN 2022年

作者： Chang, Wei Xiao, Guangchun Zhang, Hui Chen, Hui Yi, Mingdong Zhang, Jingjie Chen, Zhaoqiang Xu, Chonghai School of Mechanical and Automotive Engineering Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Key Laboratory of Equipments Manufacturing and Intelligent Measurement and Control China National Light Industry Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Shandong Institute of Mechanical Design and Research Jinan250031 China

Graphene (Gr)-reinforced Co-based (Co50) composite coatings were prepared on 40Cr steel substrates by laser cladding technology. The effects of different amounts of Gr addition on the microstructure and mechanical properties of the coating were studied. The addition of a proper amount of Gr can improve the comprehensive properties of the coating, and most Gr forms carbides, such as Cr23C6 and Cr7C3, under the action of laser irradiation. The addition of Gr can significantly refine the grains and evenly distribute them. When the addition of Gr is 3 ωt%, the average grain size is the smallest in the coating, which is 5.7 μm, and the highest microhardness reaches 777.5 HV0.2, which is an increase of 270.2% compared with the substrate. The unmelted Gr remains dispersed in the coating, which can improve lubrication and reduce friction. The average friction coefficient and wear volume are decreased to 0.335 and 4.26×107 μm3, which are approximately 54.2% and 28.0% of the substrate, respectively. © 2022, The Authors. All rights reserved.

关键词： Microstructure

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Machine-learning-aided Massive Hybrid Analog and Digital MIMO DOA Estimation for Future Wireless Networks

arXiv

引用

arXiv 2022年

作者： Shu, Feng Chen, Yiwen Zhan, Xichao Cai, Wenlong Huang, Mengxing Jie, Qijuan Li, Yifang Shi, Baihua Wang, Jiangzhou You, Xiaohu Zhao, Xinyi The School of Mathematics and Statistics Nanjing University of Science and Technology Nanjing210094 China The School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China The School of Information and Communication Engineering Hainan University Haikou570228 China The National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing100854 China The School of Engineering University of Kent CanterburyCT27NT United Kingdom The School of Southeast University Nanjing211189 China

Due to a high spatial angle resolution and low circuit cost of massive hybrid analog and digital (HAD) multiple-input multiple-output (MIMO), it is viewed as a valuable green communication technology for future wireless networks. Combining a massive HAD-MIMO with direction of arrival (DOA) will provide a high-precision even ultra-high-precision DOA measurement performance approaching the fully-digital (FD) MIMO. However, phase ambiguity is a challenge issue for a massive HAD-MIMO DOA estimation. In this paper, we review three aspects: detection, estimation, and Cramer-Rao lower bound (CRLB) with low-resolution ADCs at receiver. First, a multi-layer-neural-network (MLNN) detector is proposed to infer the existence of passive emitters. Then, a two-layer HAD (TLHAD) MIMO structure is proposed to eliminate phase ambiguity using only one-snapshot. Simulation results show that the proposed MLNN detector is much better than both the existing generalized likelihood ratio test (GRLT) and the ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV) in terms of detection probability. Additionally, the proposed TLHAD structure can achieve the corresponding CRLB using single snapshot. Copyright © 2022, The Authors. All rights reserved.

关键词： Multilayer neural networks

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Train Trajectory Optimization based on Quadratic Programming for Virtual Coupling Concepts *

Train Trajectory Optimization based on Quadratic Programming...

引用

International Conference on Intelligent Transportation

作者： Jiahao Lu Debiao Lu Baigen Cai Bin Chen Jürgen Pannek Susu Huang Frontiers Science Center for Smart High-speed Railway System Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transport School of Electronic and Information Engineering Beijing Jiaotong Universit Beijing China Frontiers Science Center for Smart High-speed Railway System Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transport School of Computer and Information Technology Beijing Jiaotong Universit Beijing China Traffic Control Technology Co. Ltd Beijing China Institute for Intermodal Transportation and Logistic System Technical University of Braunschweig Braunschweig Germany China Academy of Railway Science Corporation Limited Signal & Communication Research Institute Beijing China

The concept of virtual coupling train convoys shows promise for improving railway capacity. This approach typically involves a “leader-follower” control strategy for multiple objects, such as vehicles and drones. In order to allow followers to enter the convoy, the operation status and trajectory of the leader vehicle must be optimized. This paper examines field data collected on Guangzhou Metro Line 22, and the velocity-distance curve shows consistency among the test runs, enabling coupling possibilities. Considering constraints such as safety constraints, train dynamic model constraints, and velocity limitation constraints, when the train operating trajectory expressed by polynomial curves is incorporated into the objective function, the resulting optimization strategy can be solved using quadratic programming methods. With the optimized trajectory by the proposed method, the average acceleration decreased by 0.009 m/s 2 to 0.024 m/s 2 , and the standard deviation decreased by 0.024 m/s 2 to 0.181 m/s 2 , Using the field collected data, the paper simulates train operations under virtual coupling, leader train using the optimized train trajectory, follower train employing the pure pursuit. The correlation coefficient of the velocity time series between the leader train and the follower train is 0.9996. The headway can also be shortened to 193.15 m average and a standard deviation of 6.44 m.

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