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2nd International Conference on Control systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2020

作者： Kuvshinnikov, Vladimir Kovshov, Evgeny Sci. Eng. and Educ. Lab. of Digital Computer Systems and Automation Jsc research and Development Institute of Construction Technology-Atomstroy" Moscow Russia

ISBN: (纸本)9781728188409

It is often necessary to reduce and generalize an operating device motion paths when solving the problem of portal crane movement automation. A possible way of the specialized gantry crane operating device path planning automation using genetic search algorithms is proposed. The proposed method takes into consideration a complete set of the crane operation-routing sequence, specific movement requirements and restrictions, prohibited zones size and position. © 2020 IEEE.

关键词： Genetic algorithms

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digital engineering school on the way to digital production 1

Digital engineering school on the way to digital production

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1st International Scientific Conference on Advances in Science, Engineering and digital Education, ASEDU 2020

作者： Kovshov, E.E. Lesin, S.M. Kuvshinnikov, V.S. JSC "Research and Development Institute of Construction Technology - tomstroy" Scientific Engineering and Educational Laboratory of Digital Computer Systems and Automation Moscow Russia Moscow City University Laboratory of Research of Educational Policy of Department of the Strategic Growth Institute of System Projects Laboratory of Professional Development in Education Moscow Russia

Identifies approaches for improving and enhancing the quality of pre, basic, and additional school' engineering education according to key paradigm "Industry 4.0" based on the development and wide application of information and communication technology with opportunities in research areas of Industrial Informatics. As an example of implementation, innovative research and educational project of the digital engineering school is considered, including designed for the practical implementation of continuous engineering education "School-University-Enterprise". The main objectives of the project "digital engineering school" are formulated and disclosed, the approach to teaching programming in high-level languages using microcontrollers and microprocessor technology is highlighted, practical recommendations are given for its implementation in the structure of school education for both students and teachers. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Engineering education

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Learning Greenhouse Climate Control Policy from Monitored Data

Learning Greenhouse Climate Control Policy from Monitored Da...

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2022 Chinese automation Congress, CAC 2022

作者： Zhao, Xiaoxuan Wang, Haoyu Wang, Xiujuan Lewlomphaisarl, Udom Li, Dong Hua, Jing Kang, Mengzhen The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technologies Beijing China National Electronics and Computer Technology Center Pathum Thani Thailand Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China Qingdao AgriTech Co. Ltd. Qingdao China

ISBN: (纸本)9781665465335

The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration. © 2022 IEEE.

关键词： Greenhouses

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Special-Purpose Solid Radwaste Transfer Gantry Crane Control automation Using Genetic Algorithm

Special-Purpose Solid Radwaste Transfer Gantry Crane Control...

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International Conference on Control systems, Mathematical Modelling, automation and Energy Efficiency (SUMMA)

作者： Vladimir Kuvshinnikov Evgeny Kovshov Scientific Engineering and Educational Laboratory of Digital Computer Systems and Automation JSC "Research and Development Institute of Construction Technology - Atomstroy" Moscow Russian

ISBN: (数字)9781728188409

ISBN: (纸本)9781728181134

关键词： Cranes automation Production Solids Manufacturing Task analysis Genetic algorithms

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Stochastic-Robust Planning of Networked Hydrogen-Electrical Microgrids: A Study on Induced Refueling Demand

arXiv

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arXiv 2024年

作者： Sun, Xunhang Cao, Xiaoyu Zeng, Bo Zhai, Qiaozhu Başar, Tamer Guan, Xiaohong School of Automation Science and Engineering The Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Shaanxi Xi’an710049 China Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States Smart Integrated Energy Department Sichuan Digital Economy Industry Development Research Institute Sichuan Chengdu610037 China Department of Industrial Engineering The Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15106 United States Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing100084 China

Hydrogen-electrical microgrids are increasingly assuming an important role on the pathway toward decarbonization of energy and transportation systems. This paper studies networked hydrogen-electrical microgrids planning (NHEMP), considering a critical but often-overlooked issue, i.e., the demand-inducing effect (DIE) associated with infrastructure development decisions. Specifically, higher refueling capacities will attract more refueling demand of hydrogen-powered vehicles (HVs). To capture such interactions between investment decisions and induced refueling demand, we introduce a decision-dependent uncertainty (DDU) set and build a trilevel stochastic-robust formulation. The upper-level determines optimal investment strategies for hydrogen-electrical microgrids, the lower-level optimizes the risk-aware operation schedules across a series of stochastic scenarios, and, for each scenario, the middle-level identifies the "worst" situation of refueling demand within an individual DDU set to ensure economic feasibility. Then, an adaptive and exact decomposition algorithm, based on Parametric Column-and-Constraint Generation (PC&CG), is customized and developed to address the computational challenge and to quantitatively analyze the impact of DIE. Case studies on an IEEE exemplary system validate the effectiveness of the proposed NHEMP model and the PC&CG algorithm. It is worth highlighting that DIE can make an important contribution to the economic benefits of NHEMP, yet its significance will gradually decrease when the main bottleneck transits to other system restrictions. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Virtual reality as a tool for training specialists in the field of radiation non-destructive testing

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Journal of Physics: Conference Series 2021年第3期2094卷

作者： E E Kovshov V S Kuvshinnikov JSC 'Research and Development Institute of Construction Technology – Atomstroy' Scientific Engineering and Educational Laboratory of Digital Computer Systems and Automation Moscow Russian Federation

Organizational, technical and methodological approaches to the creation and application of virtual reality in additional education are considered. Particularly for use and development of a digital radiography simulator in non-destructive testing of products and materials. It is noted that virtual reality technologies are most widely used in training and knowledge testing of engineering and technical personnel and workers in production, as well as in technological preparation during complex and exacting operations, including products and materials testing. The pilot solutions obtained and tested to date allow us to evaluate the results of complex scientific research. The prospects of expanding the applicability range of software and hardware virtual reality solutions, including those based on network interfaces, protocols and telecommunications solutions, are determined.

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衰亡链揭示互利共生生态系统中安全与崩溃的中间阶段（英文）

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Engineering 2024年第12期 89-98页

作者：王光炜刘雪明肖颖袁烨潘林强管晓宏高建喜张海涛 The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and Technology Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi'an Jiaotong University Tsinghua National Laboratory of Information Science and Technology Department of Automation Tsinghua University Department of Computer Science Rensselaer Polytechnic Institute

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities, such as overfishing and deforestation, and the effects of such damage on ecological stability are uncertain. Despite recent advances in experimental and theoretical studies on regime shifts and tipping points, theoretical tools for understanding the extinction chain, which is the sequence of species extinctions resulting from overexploitation, are still lacking, especially for large-scale nonlinear networked systems. In this study, we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and densities. We discovered five phases during the exploitation process: safe,partial extinction, bistable, tristable, and collapse, which enabled the optimal design of restoration strategies for degraded or collapsed systems. We validated our approach using a 20-year dataset from an eelgrass restoration project. Counterintuitively, we also found a specific region in the diagram spanning exploitation rates and competition intensities, where exploiting more species helps increase *** computational tool provides insights into harvesting, fishing, exploitation, or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

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digital engineering school on the way to digital production

引用

Journal of Physics: Conference Series 2020年第1期1691卷

作者： E E Kovshov S M Lesin V S Kuvshinnikov JSC 'Research and Development Institute of Construction Technology–Atomstroy' Scientific Engineering and Educational Laboratory of Digital Computer Systems and Automation Moscow Russian Federation Moscow City University Laboratory of research of educational policy of Department of the strategic growth Institute of system projects Laboratory of professional development in education Moscow Russian Federation

Identifies approaches for improving and enhancing the quality of pre, basic, and additional school' engineering education according to key paradigm 'Industry 4.0' based on the development and wide application of information and communication technology with opportunities in research areas of Industrial Informatics. As an example of implementation, innovative research and educational project of the digital engineering school is considered, including designed for the practical implementation of continuous engineering education 'School-University-Enterprise'. The main objectives of the project 'digital engineering school' are formulated and disclosed, the approach to teaching programming in high-level languages using microcontrollers and microprocessor technology is highlighted, practical recommendations are given for its implementation in the structure of school education for both students and teachers.

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

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The Innovation 2025年第6期6卷

作者： Jincai Huang Yongjun Xu Qi Wang Qi (Cheems) Wang Xingxing Liang Fei Wang Zhao Zhang Wei Wei Boxuan Zhang Libo Huang Jingru Chang Liantao Ma Ting Ma Yuxuan Liang Jie Zhang Jian Guo Xuhui Jiang Xinxin Fan Zhulin An Tingting Li Aiguo Fei Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China National Engineering Research Center for Software Engineering Peking University Beijing 100871 China College of Systems Engineering National University of Defense Technology Changsha 410073 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing 100081 China Laboratory for Big Data and Decision National University of Defense Technology Changsha 410073 China School of Automation Beijing Institute of Technology Beijing 100081 China Huazhong University of Science and Technology Wuhan 430074 China University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of AI Safety Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China School of Information Science and Engineering Dalian Polytechnic University Dalian 116034 China The Hong Kong University of Science and Technology (Guangzhou) Guangzhou 511453 China College of Information and Electrical Engineering China Agricultural University Beijing 100083 China State Key Laboratory of Efficient Utilization of Agricultural Water Resources Beijing 100083 China IDEA Research International Digital Economy Academy Shenzhen 518057 China School of Computer Science National Pilot Software Engineering School Beijing University of Posts and Telecommunications Beijing 100876 China

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.

关键词： artificial intelligence intelligent decision-making foundation models agent large language model

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Machine discovery of partial differential equations from spatiotemporal data

arXiv

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arXiv 2019年

作者： Yuan, Ye Li, Junlin Li, Liang Jiang, Frank Tang, Xiuchuan Zhang, Fumin Liu, Sheng Goncalves, Jorge Voss, Henning U. Li, Xiuting Kurths, Jürgen Ding, Han School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30332 United States School of Power and Mechanical Engineering Wuhan University Wuhan430074 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Luxembourg Centre for Systems Biomedicine University of Luxembourg BelvauxL-4367 Luxembourg Citigroup Biomedical Imaging Center Weill Cornell Medical College New York10021 United States Research Domain IV - Transdisciplinary Concepts & Methods Potsdam Institute for Climate Impact Research Potsdam14473 Germany School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal System Discovery (S3d), decides which physical terms are necessary and which can be removed (because they are physically negligible in the sense that they do not affect the dynamics too much) from a pool of candidate functions. The method is built on the recent development of Sparse Bayesian Learning;which enforces the sparsity in the to-be-identified PDEs, and therefore can balance the model complexity and fitting error with theoretical guarantees. Without leveraging prior knowledge or assumptions in the discovery process, we use an automated approach to discover ten types of PDEs, including the famous Navier-Stokes and sine-Gordon equations, from simulation data alone. Moreover, we demonstrate our data-driven discovery process with the Complex Ginzburg-Landau Equation (CGLE) using data measured from a traveling-wave convection experiment. Our machine discovery approach presents solutions that has the potential to inspire, support and assist physicists for the establishment of physical laws from measured spatiotemporal data, especially in notorious fields that are often too complex to allow a straightforward establishment of physical law, such as biophysics, fluid dynamics, neuroscience or nonlinear optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear optics

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