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Relation Model of Burden Operation and State Variables of Blast Furnace Based on Low Frequency Feature Extraction*

IFAC-PapersOnLine 2017年第1期50卷 13796-13801页

作者： Zhang, Kexin Wu, Min An, Jianqi Cao, Weihua Liu, Zhentao Ning, Fulong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

In the blast furnace ironmaking process, the running state of the blast furnace can be directly adjusted by the burden operation. Therefore, the explicit relation between the burden operation and the running state variables is vital for the blast furnace operators. However, the state variables of the blast furnace are affected by many factors and the burden matrix is complicated. In this paper, a support vector regression(SVR) predicting model based on low frequency feature extraction is proposed to solve these problems. First, the low frequency components of state variables time series which are mostly affected by the burden operation are extracted. Then, the dimensions of the burden matrix are reduced by a devised simple expression method. Finally, the relation model based on SVR is proposed to predict the values of the expected state variables according to the simplified burden matrix and the value of initial state variables. The simulation on real factory data indicates that the model reflects the accurate quantitative relation between the burden operation and the state variables. © 2017

关键词： Blast furnaces Blast furnace practice Extraction Feature extraction Support vector regression Blast furnace iron making Blast furnace operators burden operation Initial state variables Low frequency components Relation models State variables Support vector regression (SVR)

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Evolutionary dynamics of cryptocurrency transaction networks: An empirical study

arXiv

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arXiv 2018年

作者： Liang, Jiaqi Li, Linjing Zeng, Daniel State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Department of Management of Information Systems University of Arizona TucsonAZ United States

Cryptocurrency is a well-developed blockchain technology application that is currently a heated topic throughout the world. The public availability of transaction histories offers an opportunity to analyze and compare different cryptocurrencies. In this paper, we present a dynamic network analysis of three representative blockchain-based cryptocurrencies: Bitcoin, Ethereum, and Namecoin. By analyzing the accumulated network growth, we find that, unlike most other networks, these cryptocurrency networks do not always densify over time, and they are changing all the time with relatively low node and edge repetition ratios. Therefore, we then construct separate networks on a monthly basis, trace the changes of typical network characteristics (including degree distribution, degree assortativity, clustering coefficient, and the largest connected component) over time, and compare the three. We find that the degree distribution of these monthly transaction networks cannot be well fitted by the famous power-law distribution, at the same time, different currency still has different network properties, e.g., both Bitcoin and Ethereum networks are heavy-tailed with disassortative mixing, however, only the former can be treated as a small world. These network properties reflect the evolutionary characteristics and competitive power of these three cryptocurrencies and provide a foundation for future research. Copyright © 2018, The Authors. All rights reserved.

关键词： Blockchain

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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Innovation 2025年第6期6卷 100948页

作者： Huang, Jincai Xu, Yongjun Wang, Qi Wang, Qi [Cheems] Liang, Xingxing Wang, Fei Zhang, Zhao Wei, Wei Zhang, Boxuan Huang, Libo Chang, Jingru Ma, Liantao Ma, Ting Liang, Yuxuan Zhang, Jie Guo, Jian Jiang, Xuhui Fan, Xinxin An, Zhulin Li, Tingting Li, Xuefei Shao, Zezhi Qian, Tangwen Sun, Tao Diao, Boyu Yang, Chuanguang Yu, Chenqing Wu, Yiqing Li, Mengxian Zhang, Haifeng Zeng, Yongcheng Zhang, Zhicheng Zhu, Zhengqiu Lv, Yiqin Li, Aming Chen, Xu An, Bo Xiao, Wei Bai, Chenguang Mao, Yuxing Yin, Zhigang Gui, Sheng Su, Wentao Zhu, Yinghao Gao, Junyi He, Xinyu Li, Yizhou Jin, Guangyin Ao, Xiang Zhai, Xuehao Tan, Haoran Yun, Lijun Shi, Hongquan Li, Jun Fan, Changjun Huang, Kuihua Harrison, Ewen Leung, Victor C.M. Qiu, Sihang Dong, Yanjie Zheng, Xiaolong Wang, Gang Zheng, Yu Wang, Yuanzhuo Guo, Jiafeng Wang, Lizhe Cheng, Xueqi Wang, Yaonan Yang, Shanlin Fu, Mengyin Fei, Aiguo Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Huazhong University of Science and Technology Wuhan430074 China School of Automation Beijing Institute of Technology Beijing100081 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing100081 China Guangzhou511453 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China IDEA Research International Digital Economy Academy Shenzhen518057 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Science National University of Defense Technology Changsha410073 China Center for Systems and Control College of Engineering Peking University Beijing100871 China Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China College of Systems Engineering National University of Defense Technology Changsha410073 China Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Electrical Engineering Chongqing University Chongqing400044 China Department of Mathematics The University of Hong Kong Hong Kong SAR999077 China School of Food Science and Technology Dalian Polytechnic University Dalian116034 China Centre for Medical Informatics University of Edinburgh EdinburghEH16 4UX United Kingdom Department of Stomatology Peking Union Medical College Hospital Chinese Academ

Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM's evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. © 2025 The Authors

关键词： Reinforcement learning

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Scientific-practical results of monitoring anthropogenic influence upon environment of mining territories

Scientific-practical results of monitoring anthropogenic inf...

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2018 Ukrainian School of Mining Engineering, USME 2018

作者： Kachurin, Nikolay Komaschenko, Vitaliy Golik, Vladimir Morkun, Volodymyr Tula State University Department of Geotechnologies and Underground Constructions 92 Lenina Ave. Tula300012 Russia Belgorod State National Research University Trade-union St. Belgorod117485 Russia North Caucasus Mining Metallurgical Institute 85 Pobedy St. Vladikavkaz308015 Russia Kryvyi Rih National University Computer Science Automation and Control Systems Department 11 Vitalii Matusevych St. Kryvyi Rih50027 Ukraine

The objective of this paper is to improve the ecological monitoring system and to take effective technological measures by way of wastes neutralization. The scientific-practical results of monitoring the anthropogenic influence upon the environment of mining-industrial territories were discussed. The global environmental problems of modernity are connected only with the anthropogenic pollution of the atmosphere. Pollution by hazardous substances at various enterprises harms health and disrupts the dynamic balance of natural systems. It is especially typical for mining-industrial region territories. The solution of the problem of environmentally optimal distributing resources for industrial enterprises of the mining-industrial region will allow making maximal profit from each enterprise by assumption of reducing anthropogenic influence upon environment up to the maximum permissible value, which is specified by normative documents. The patterns of formation of mining enterprises influence consequences on the atmosphere have been improved with the use of experimental and theoretical studies and in order to optimize the resources distribution for preventive measures, which can ensure the atmospheric safety of the mining-industrial region. The proposed methodological principles for a comprehensive assessment of the atmosphere of the mining-industrial region allow to implement an integrated approach to forecasting the intensity of atmospheric pollution, the economic efficiency of production and atmospheric air condition control, using the basic requirements of the environmental imperative for the territory under consideration. © 2018 The Authors, published by EDP Sciences.

关键词： Accident prevention

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Optimal DoS Attack Strategy against Remote State Estimation Over Lossy Networks 29

Optimal DoS Attack Strategy against Remote State Estimation ...

引用

第29届中国控制与决策会议

作者： Menglin Li Jiahu Qin Ling Shi Xinghuo Yu Huijun Gao Department of Automation University of Science and Technology of China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology School of Engineering RMIT University Research Institute of Intelhgent Control and Systems Harbin Institute of Technology

ISBN: (纸本)9781509046584

This paper considers a Denial-of-Service(DoS) attack scheduling ***,a sensor employs the wireless fink to send the data packet to the remote estimator at each time step,while an energy-constrained attacker launches DoS attacks against the remote state estimation,and designs an optimal attack strategy to maximize damage to the remote estimation *** packet will drop if the channel is *** most of the existing works on DoS attacks,it is assumed that the wireless channel is perfect,i.e.,the packet dropout never occurs in the absence of ***,this is far from the practical *** encompass the lossy nature of wireless networks,we study the scenario of lossy networks in which the packet may drop even without attack,and construct the optimal attack strategy that maximizes the average expected estimation error at the remote estimator over lossy *** simulations are provided to demonstrate the effectiveness of the theoretical results.

关键词： Cyber-Physical Systems DoS attack lossy networks energy constraint remote state estimation

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Closed Loop Fault Detectability Based on a Gap-Metric

Closed Loop Fault Detectability Based on a Gap-Metric

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control Technology and Applications (CCTA),

作者： André Sekunda Steven Ding Niels Kjølstad Poulsen Henrik Niemann Department of Electrical Engineering Automation and Control Tech. University of Denmark Denmark Dept. of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany Dept. of Applied Mathematics and Computer Science Tech. University of Denmark Kgs. Lyngby Denmark

Systems are often controlled using feedback loops. Fault diagnosis schemes are usually designed assuming that there is no feedback loop. Therefore fault diagnosis methods need to accommodate for the feedback loop. One such method is active fault diagnosis based on a fault signature system. This method is derived using the YJBK parametrisation, named after Youla, Jabr, Bongiorno and Kucera. It uses the derived fault signature system to determine the detectability of possible faults in the system. Deriving the fault signature system requires knowledge about the controller. This paper demonstrates the possibility of estimating the detectability of faults in the fault signature system using a gap-metric. The gap-metric has the advantage of only requiring knowledge about the plant. By using the gap-metric it is possible to estimate the detectability of faults without using information about the controller.

关键词： Fault diagnosis Measurement Kernel Closed loop systems Fault detection Sensors

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Efficient visual loop closure detection in different times of day

Efficient visual loop closure detection in different times o...

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Intelligent Robotics and Industrial Applications using computer Vision 2017, IRIACV 2017

作者： Erhan, Can Sariyanidi, Evangelos Sencan, Onur Temeltas, Hakan Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom

Performing reliable and computationally efficient loop closure detection in real-world environments still remains a challenging problem. In this paper, we propose a novel method for efficient loop closure detection in different times of day. An illumination invariant color transform is applied to images that are represented by a whole-image descriptor, named PALM. The efficiency of our method resides either in description of the places or in image matching in which FLANN is used for fast nearest neighbor search. With this approach, searching time is decreased about 70 times compared to standard brute-force search with no significant loss of accuracy. According to the experiments that are performed in real-world datasets, the proposed method successfully accomplishes to detect loops under varied illumination conditions with high accuracy, and it allows real-time operation for long-life localization and mapping. © 2017, Society for Imaging Science and Technology.

关键词： Nearest neighbor search

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Crowdsensing game with demand uncertainties: A deep reinforcement learning approach

arXiv

引用

arXiv 2018年

作者： Zhan, Yufeng Xia, Yuanqing Zhang, Jiang Li, Ting Wang, Yu School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Lab Department of Computer Science University of North Carolina at Charlotte CharlotteNC28223 United States

Currently, explosive increase of smartphones with powerful built-in sensors such as GPS, accelerometers, gyroscopes and cameras has made the design of crowdsensing applications possible, which create a new interface between human beings and life environment. Until now, various mobile crowdsensing applications have been designed, where the crowdsourcers can employ mobile users (MUs) to complete the required sensing tasks. In this paper, emerging learning-based techniques are leveraged to address crowdsensing game with demand uncertainties and private information protection of MUs. Firstly, a novel economic model for mobile crowdsensing is designed, which takes MUs' resources constraints and demand uncertainties into consideration. Secondly, an incentive mechanism based on Stackelberg game is provided, where the sensing-platform (SP) is the leader and the MUs are the followers. Then, the existence and uniqueness of the Stackelberg Equilibrium (SE) is proven and the procedure for computing the SE is given. Furthermore, a dynamic incentive mechanism (DIM) based on deep reinforcement learning (DRL) approach is investigated without knowing the private information of the MUs. It enables the SP to learn the optimal pricing strategy directly from game experience without any prior knowledge about MUs' information. Finally, numerical simulations are implemented to evaluate the performance and theoretical properties of the proposed mechanism and approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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Data-driven gradient algorithm for high-precision quantum control

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Physical Review A 2018年第4期97卷 042122-042122页

作者： Re-Bing Wu Bing Chu David H. Owens Herschel Rabitz Department of Automation Tsinghua University Beijing 100084 China Center for Quantum Information Science and Technology BNRist Beijing 100084 China School of Electronic and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom Department of Automation Zhengzhou University Zhengzhou 450001 China Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom Department of Chemistry Princeton University Princeton 08544 NJ United States

In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., grape) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that grape can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-grape) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-grape algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit controlled-not gate.

关键词： Quantum control Quantum gates

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Self-organized Task Allocation in a Swarm of E-puck Robots

Self-organized Task Allocation in a Swarm of E-puck Robots

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2017中国智能自动化会议(CIAC 2017)

作者： Qiaoyu Li Xiaolong Yang Yuying Zhu Jianlei Zhang Department of Automation College of Computer and Control Engineering Nankai University

1 Introduction The study on task allocation behaviors realized by self-organization receives much attention nowadays,which has a wide range of applications in artificial intelligence and engineering *** of labor,where thousands of individuals in nature perform specific tasks can be seen as the hallmark of insect societies [1–3].Daily experience tells us that the division of labor is a common phenomenon,in which

关键词： Swarm Self-organized Task Allocation in a Swarm of E-puck Robots

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