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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Miao Ye, Peijun Liu, Xudong Liu, Sheng Xiong, Gang Zhang, Liguo Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

ISBN: (纸本)9781665433372

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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Fast calibration of agent-based model using mean-field approach 1

Fast calibration of agent-based model using mean-field appro...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Lu, Wanze Xiong, Gang Liu, Xudong Liu, Sheng Ye, Peijun Zhang, Liguo Beijing University of Technology Faculty of Information and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

Calibration of simulation system is an important step to establish a reliable simulation system. In this paper, based on the existing mean field calibration theory, a new fast calibration method for complex urban traffic system based on mean field method is discussed by establishing the relationship between the macroscopic observation quantity and the proxy microscopic parameters. This method makes use of the machine learning method, and reduces the dimension of the state vector in the discrete time period, so that the dimension of the macroscopic state transition matrix is lower, and then reduces the computational complexity of the system calibration. Finally, the calibration results of the simulation system were verified by SUMO traffic simulation software. © 2021 IEEE.

关键词： Calibration

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Thermal-aware Energy Efficient Task Scheduling Framework

Thermal-aware Energy Efficient Task Scheduling Framework

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Jian Nong Jia Chen Yinqing Wang Wei Qin Xi He Faculty of Innovation Engineering-School of Computer Science and Engineering Macau University of Science and Technology Macau China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Guangxi Colleges and Universities Key Laboratory of Industry Software Technology Wuzhou University Wuzhou China High Performance Computing Lab Wuzhou University Wuzhou China

Large energy consumption in data centers has become a challenging problem with the emergence of cloud computing and large scale data centers. In this paper, we present an architectural framework for thermal-aware resource management while considering energy efficiency. The framework consists of a layered architecture and integrates a set of easy-to-use client tools and a thermal-aware task management middleware to schedule tasks based on thermal conditions within a cluster and among different data centers. As part of this paper we focus on the development of a thermal-aware task scheduling component for a single data center. This component is fundamental to our future activities, while considering to balance the temperature distribution in a single data center, thus implicitly minimizing energy cost in data centers.

关键词： Data centers Temperature distribution Schedules Processor scheduling Thermal management Ubiquitous computing Energy efficiency

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Proximal-like algorithms for equilibrium seeking in mixed-integer Nash equilibrium problems

Proximal-like algorithms for equilibrium seeking in mixed-in...

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IEEE Conference on Decision and control

作者： Filippo Fabiani Barbara Franci Simone Sagratella Martin Schmidt Mathias Staudigl Department of Engineering Science University of Oxford United Kingdom IMT School for Advanced Studies Lucca Lucca Italy Department of Advanced Computing Sciences Maastricht University Maastricht The Netherlands Department of Computer Control and Management Engineering Antonio Ruberti (DIAG) Sapienza University of Rome Rome Italy Department of Mathematics at Trier University Universitätsring 15 54296 Trier Germany

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider potential games with mixed-integer variables, for which we propose two distributed, proximallike equilibrium seeking algorithms. Specifically, we focus on two scenarios: i) the underlying game is generalized ordinal and the agents update through iterations by choosing an exact optimal strategy; ii) the game admits an exact potential and the agents adopt approximated optimal responses. By exploiting the properties of integer-compatible regularization functions used as penalty terms, we show that both algorithms converge to either an exact or an ϵ-approximate equilibrium. We corroborate our findings on a numerical instance of a Cournot oligopoly model.

关键词： Computational modeling Measurement uncertainty Stochastic processes Games Approximation algorithms Nash equilibrium Cost function

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Data-Driven Estimation of Infinitesimal Generators of Stochastic Systems ⁎

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IFAC-PapersOnLine 2021年第5期54卷 277-282页

作者： Ameneh Nejati Abolfazl Lavaei Sadegh Soudjani Majid Zamani Department of Electrical Engineering Technical University of Munich Germany Institute for Dynamic Systems and Control ETH Zurich Switzerland School of Computing Newcastle University United Kingdom Department of Computer Science University of Colorado Boulder USA and LMU Munich Germany

This paper is concerned with a data-driven approach for the estimation of infinitesimal generators of continuous-time stochastic systems with unknown dynamics. We first approximate the infinitesimal generator of the solution process via a set of data collected from trajectories of the unknown system. The approximation utilizes both time discretization and sampling from the solution process. Assuming proper continuity assumptions on dynamics of the system, we then quantify the closeness between the infinitesimal generator and its approximation while providing a priori guaranteed confidence bound. We demonstrate that both the time discretization and the number of data play significant roles in providing a reasonable closeness precision. Moreover, for a fixed size of data, variance of the estimation converges to infinity when the time discretization parameter goes to zero. The formulated error bound shows how to pick proper data size and time discretization jointly to prevent this counter-intuitive behavior. The proposed results are demonstrated on a case study.

关键词： Continuous-time stochastic systems Data-driven estimation Infinitesimal generators

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Multiscale feature decoupling via VMD and dual-channel networks for dissolved gas prediction in transformers

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Electric Power Systems Research 2025年 248卷

作者： Haijun Xiong Yahan Li Yiji Meng Junping Wang Yutian Wang School of Control and Computer Engineering North China Electric Power University Baoding 071003 Hebei China Hebei Key Laboratory of Knowledge Computing for Energy & Power Baoding 071003 Hebei China

To address the impact of the non-linearity and non-stationarity of transformer oil dissolved gas concentration sequences on prediction accuracy, a multi-scale hybrid prediction framework based on VMD optimized by PSO and deep learning is proposed. By introducing a sliding average pooling operation method, the subsequences obtained from VMD decomposition are further decoupled into long-term trend and residual components, establishing a dual-channel heterogeneous modeling system. BiGRU is employed to capture the trend component, while TCN integrated with a multi-head self-attention mechanism is designed to enhance the dynamic representation capability of key time points in the residual component, enabling the collaborative optimization of multi-scale features. Experimental results show that the proposed model outperforms traditional methods in predicting dissolved gas C 2 H 2 in transformer oil, with a reduction in RMSE by 0.2918, a decrease in MAPE by 23.78%, and an improvement in R 2 by 37.25%. Predictions of other gas components, such as H 2 and total hydrocarbons, further demonstrate that the model exhibits strong generalization performance across various gas components.

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Penetration trajectory optimization for the hypersonic gliding vehicle encountering two interceptors

arXiv

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arXiv 2022年

作者： Shen, Zhipeng Yu, Jianglong Dong, Xiwang Hua, Yongzhao Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

The penetration trajectory optimization problem for the hypersonic gliding vehicle (HGV) encountering two interceptors is investigated. The HGV penetration trajectory optimization problem considering the terminal target area is formulated as a nonconvex optimal control problem. The nonconvex optimal control problem is transformed into a second-order cone programming (SOCP) problem, which can be solved by state-of-the-art interior-point methods. In addition, a penetration strategy that only requires the initial line-of-sight angle information of the interceptors is proposed. The convergent trajectory obtained by the proposed method allows the HGV to evade two interceptors and reach the target area successfully. Furthermore, a successive SOCP method with a variable trust region is presented, which is critical to balancing the trade-off between time consumption and optimality. Finally, the effectiveness and performance of the proposed method are verified by numerical simulations. Copyright © 2022, The Authors. All rights reserved.

关键词： Numerical methods

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A Comprehensive Analysis in Investigating the Impact of Big Data Analytics in Wireless Networks in Failure Prediction, Prevention and Recovery 2

A Comprehensive Analysis in Investigating the Impact of Big ...

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2nd International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2022

作者： Surya, S. Rajasekaran, P. Yuriy, Shvets Johar, Siti Sarawati Tripathi, Amrendra Magno Ventayen, Randy Joy Computer Science and Engineering School of Computing Kalasalingam University India Information Technology Dr. N.G.P Institute of Technology India Financial University under the Goverment of Russian Federation Institute of Control of Science Ras Moscow Russia Centre for General Studies and Co-curricular Universiti Tun Hussein Onn Malaysia Department of Social Science Parit Raja Johor Darul Takzim Batu Pahat86400 Malaysia School of Computer Science Upes Dehradun India Pangasinan State University Lingayen Campus Philippines

ISBN: (纸本)9781665437899

The current economic and competitive environment has enabled many businesses and industries to implement digital for enhancing the business operations and support in addressing the overall objectives. Dur to this there is a mounting avalanche information being shared between the individuals, companies and governments, the increase in the usage of mobile devices, internet, social media and other ecommerce services has supported in increasing the volume of data. This trend is expected to grow exponentially and hence there is a requirement to provide wireless network in an effective manner, the increased usage of data and information has resulted in facing various failures, like call drops for mobile users, low bandwidth for internet users etc. Hence, it is highly necessary to implement tools to understand the failure prediction, prevention and recovery on the network. Hence, this study is focused in investigating the impact of big data analysis in protecting the wireless networks from such failures and support in processing large volume of information in an effective manner, the big data analytics can also extract useful data will enable in addressing the concerned parties so as to make critical decisions. In this study, the researcher intends to conduct the survey using closed ended questionnaire from the individuals so as to measure the effectiveness of applying big data for failure prevention, protection and recovery in the wireless network. © 2022 IEEE.

关键词： Wireless networks

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A Power Grid Start-Up Work Ticket Event Extraction Method Based on Domain Knowledge Graph Enhanced Model 2

A Power Grid Start-Up Work Ticket Event Extraction Method Ba...

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2nd International Conference on Electronic Materials and Information engineering, EMIE 2022

作者： Qiu, Longgang Ping, Yuan Zhang, Yue Jiang, Guangji Huang, Shuai Zhang, Yong Deng, Min Chen, Congtan Zhang, Pei Rao, Guozheng State Grid Huainan Electric Power Supply Company Anhui Province Huainan232000 China NARI Group Corporation Co. Ltd. State Grid Electric Power Research Institute Co. Ltd. Jiangsu Province Nanjing211106 China Beijing KeDong Electric Power Control System Co. Ltd. Haidian District Beijing100192 China School of Electrical Engineering Beijing Jiaotong University Beijing100091 China College of Intelligence and Computing Tianjin University Tianjin300350 China

ISBN: (纸本)9781713865629

The power grid start-up work ticket event extraction has excellent challenges in its text mining. However, exiting extraction models usually rely on hand-crafted features and ignore the domain knowledge. To better understand the context knowledge of the power grid start-up work ticket, we propose a power grid start-up work ticket event extraction method based on domain knowledge graph enhanced model. Our model has several features. First, our model is a joint end-to-end model. It helps to jointly perform both trigger detection and argument detection with shared parameters. Second, we integrate CNN and Bi-LSTM-CRF to detect event triggers. Third, we propose Conceptual Context Tree-LSTM (CC Tree-LSTM) with the shortest path to detect event arguments. Multiple experiments have proved that the framework of this paper is superior to other comparison methods in the Precision, Recall, and F1 score of event extraction tasks. The Precision, Recall, and F1 score of our model reach 0.8032, 0.8127, and 0.8079. It verifies the feasibility and effectiveness of the method. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Extraction

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Hierarchical Bit-Wise Differential Coding (HBDC) of Point Cloud Attributes

Hierarchical Bit-Wise Differential Coding (HBDC) of Point Cl...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yan Huang Bin Wang C.-C. Jay Kuo Hui Yuan Jingliang Peng School of Software Shandong Universtiy University of Southern California School of Control Science and Engineering Shandong Universtiy Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan School of Information Science and Engineering University of Jinan

Targeting both computing and coding efficiencies, we propose in this work a novel hierarchical bit-wise differential coding scheme to compress point cloud attributes. The encoder firstly quantizes and organizes the points into an octree structure and, for each internal node, picks its attribute(s) from a child named source child. Next, the encoder conducts a top-down scanning of the hierarchy. For each node with more than one child, it computes the bit-wise attribute difference between the current node and each non-source child by exclusive-OR and encodes the difference with an arithmetic coder. Further, a table look-up approach is proposed to accelerate the online source child identification. The proposed scheme produces superior computing and coding efficiencies for lossless point cloud attribute compression, outperforming the MPEG benchmark coders by large margins in our experiments.

关键词： Three-dimensional displays Image color analysis Conferences Octrees Transform coding Benchmark testing Signal processing

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