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Parallel Building: A Complex System Approach for Smart Building Energy Management

IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1452-1461页

作者： Abdulaziz Almalaq jun Hao jun jason zhang Fei-Yue Wang Department of Electrical Engineering Engineering CollegeUniversity of HailHail 55476Saudi Arabia Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of DenverDenverCO 80208 USA State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 and also with the Research Center for Military Computational Experiments and Parallel Systems TechnologyNational University of Defense TechnologyChangsha 410073China

These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5 G, the ACP theory(i.e., artificial systems,computational experiments, and parallel computing) will play a much more crucial role in modeling and control of complex systems like commercial and academic buildings. The necessity of making accurate predictions of energy consumption out of a large number of operational parameters has become a crucial problem in smart buildings. Previous attempts have been made to seek energy consumption predictions based on historical data in buildings. However, there are still questions about parallel building consumption prediction mechanism using a large number of operational parameters. This article proposes a novel hybrid deep learning prediction approach that utilizes long short-term memory as an encoder and gated recurrent unit as a decoder in conjunction with ACP theory. The proposed approach is tested and validated by real-world dataset, and the results outperformed traditional predictive models compared in this paper.

关键词： ACP theory artificial intelligence data acquisition deep learning(DL) energy consumption machine learning parallel energy prediction prediction algorithms smart grid

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Parallel intelligence： toward lifelong and eternal developmental AI and learning in cyber-physical-social spaces

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Frontiers of Computer Science 2018年第3期12卷 401-405页

作者： Fei-Yue WANG jun jason zhang Xiao WANG The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Electrical Engineering Wuhan University Wuhan 430072 China Qingdao Academy of Intelligent Industries Qingdao 266109 China

Dear editor, Fundamentally, there are only two main approaches so far in artificial intelligence （AI）： reasoning-oriented formal logic approach and function-oriented computational intelligence approach, so called Neats vs. Scuruffies, which is a reflection of the historical fight between two schools of thought for formalism and empiricism respectively in the field of AI that is continuing even today.

关键词： FRAMEWORK

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Parallel Dispatch:A New Paradigm of Electrical Power System Dispatch

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 311-319页

作者： jun jason zhang Fei-Yue Wang Qiang Wang Dazhi Hao Xiaojing Yang David Wenzhong Gao Xiangyang Zhao Yingchen zhang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver Denver 80210 CO USA State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science (SKL-MCCS CASIA) Beijing 100190 China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha 410073 China State Grid Tianjin Electric Power Company Tianjin 300010 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China National Renewable Energy Laboratory Golden CO 80401 USA IEEE

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

关键词： ACP knowledge automation power dispatch parallel dynamic programming parallel intelligence paralle learning situational awareness

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Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 113-120页

作者： Fei-Yue Wang jun jason zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie zhang Liuqing Yang IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology the Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver the Department of Computer Science and Engineering University of Minnesota the Qingdao Academy of Intelligent Industries (QAII) Qingdao Shandong China and SKL-MCCS CASIA the Department of Electrical and Computer Engineering Colorado State University

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of Automation.

关键词： Religious buildings

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Call for Papers SEE Special Issueon"Hybrid-augmented Intelligence in Power Systems Operation and Control"

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CSEE Journal of Power and Energy Systems 2022年第6期8卷 I0001-I0001,F0003页

作者： Guo jianbo Hamed Mohsenian-Rad jun jason zhang State Grid Corporation of China China Universityof California at Riverside USA Wuhan University China

Power systems operation and control is concerned essentially with the cognition,management,and control(CMC)process for complex power systems.A power system with high a penetration rate of renewable energies,i.e.,the"Next-Generation Power Systems",has featured characteristics of open operational environments,complex system components,diverse operational modes,tightly coupled component behaviours,stringent demand on real-time response performance,high criticality.

关键词： Hybrid Power system

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Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence:mechanisms and applications of cognition,management,and control for complex systems

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Frontiers of Information Technology & Electronic Engineering 2022年第8期23卷 1142-1157页

作者： Fei-Yue WANG Jianbo GUO Guangquan BU jun jason zhang The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Grid Cooperation of China Beijing 100031China China Electric Power Research Institute Beijing 100192China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine *** need for using human-machine HAI in complex systems is then explained in *** concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid *** is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.

关键词： Complex systems Human-machine knowledge automation Parallel systems Bulk power grid dispatch Artificial intelligence Internet of Minds(IoM)

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： jun jason zhang David Wenzhong Gao Yingchen zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 150-162页

作者： jun Zha Huijie zhang School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China Xi’an Jiaotong University Suzhou Academy Suzhou 215123China

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial *** propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine *** method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement *** consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic *** four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization *** experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser *** a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed *** research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

关键词： Multi-point positioning Multi-station synchronization CNC machine tool Geometric error Error separation

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Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao zhang Ying FU jun zhang School of Computer Science and Technology Beijing Institute of Technology Advanced Reasearch Institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing

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Host plant traits play a crucial role in shaping the composition of epiphytic microbiota in the arid desert,Northwest China

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Journal of Arid Land 2024年第5期16卷 699-724页

作者： zhang jun zhang Yuanming zhang Qi State Key Laboratory of Desert and Oasis Ecology Key Laboratory of Ecological Safety and Sustainable Development in Arid LandsXinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China Xinjiang Key Laboratory of Biodiversity Conservation and Application in Arid Lands Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China Xinjiang Field Scientific Observation Research Station of Tianshan Wild Fruit Forest Ecosystem Yili Botanical GardenXinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China College of Life Sciences Shihezi UniversityShihezi 832003China

Phyllosphere microorganisms are a crucial component of environmental microorganisms,highly influenced by host characteristics,and play a significant role in plant health and ***,the impact of host characteristics on shaping phyllosphere microbial communities of plants with different life forms remains *** high-throughput sequencing technology,this study analyzed the diversity and community composition of phyllosphere epiphytic microorganisms(e.g.,bacteria and fungi)of various plant life forms in the hinterland of the Gurbantunggut Desert,Northwest *** annotation of prokaryotic taxa(FAPROTAX)and fungi function guild(FUNGuild)were employed to assess the ecological functions of microorganisms and to investigate the role of stochastic and deterministic processes in shaping phyllosphere microbial *** showed a diverse array of phyllosphere epiphytic microorganisms in the desert plants,with Proteobacteria,Cyanobacteria,and Actinobacteriota dominating bacterial community,while Ascomycota and Basidiomycota were prevalent in fungal *** across different plant life forms highlighted distinct microbial communities,indicating strong filtering effects by plant *** prediction identified intracellular parasites(accounting for 27.44%of bacterial community abundance),chemoheterotrophy(10.12%),and phototrophy(17.41%)as the main functions of epiphytic bacteria on leaves of different life form *** prediction indicated that phyllosphere epiphytic fungi primarily served as Saprotrophs(81.77%),Pathotrophs(17.41%),and Symbiotrophs(0.82%).Co-occurrence network analysis demonstrated a predominance of positive correlations among different microbial ***-Crick dissimilarity index analysis revealed that deterministic processes predominantly influenced phyllosphere bacterial and fungal community *** partitioning analysis and random forest modeling suggested that pla

关键词： phyllosphere epiphytic bacteria phyllosphere epiphytic fungi community structure community diversity functional diversity plant life form plant functional traits

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