The integration of industrial Internet,cloud computing,and big data technology is changing the business and management mode of the industry ***,the industry chain is characterized by a wide range of fields,complex env...
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The integration of industrial Internet,cloud computing,and big data technology is changing the business and management mode of the industry ***,the industry chain is characterized by a wide range of fields,complex environment,and many factors,which creates a challenge for efficient integration and leveraging of industrial big *** at the integration of physical space and virtual space of the current industry chain,we propose an industry chain digital twin(DT)system framework for the industrial *** addition,an industry chain information model based on a knowledge graph(KG)is proposed to integrate complex and heterogeneous industry chain data and extract industrial ***,the ontology of the industry chain is established,and an entity alignment method based on scientific and technological achievements is ***,the bidirectional encoder representations from Transformers(BERT)based multi-head selection model is proposed for joint entity–relation extraction of industry chain ***,a relation completion model based on a relational graph convolutional network(R-GCN)and a graph sample and aggregate network(GraphSAGE)is proposed which considers both semantic information and graph structure information of *** results show that the performances of the proposed joint entity–relation extraction model and relation completion model are significantly better than those of the ***,an industry chain information model is established based on the data of 18 industry chains in the field of basic machinery,which proves the feasibility of the proposed method.
Modern Graphics Processing Units (GPUs) demand life expectancy extended to many years, exposing the hardware to aging (i.e., permanent faults arising after the end-of-manufacturing test). Hence, techniques to assess p...
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Integrated access and backhaul (IAB) is a promising solution to improve coverage at low deployment costs. In IAB networks, due to wireless channel variations, guaranteeing delay for delay-sensitive applications is a m...
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With the aid of the subspace technique and the average consensus algorithm, the main objective of this article is to develop a data-driven design of distributed fault detection for dynamic systems using the measuremen...
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With the aid of the subspace technique and the average consensus algorithm, the main objective of this article is to develop a data-driven design of distributed fault detection for dynamic systems using the measurement in a complex sensor network. Specifically, the design process consists of two stages: distributed off-line learning and distributed online fault detection. Among them, the distributed off-line learning stage involves the average consensus algorithm and parameter identification by subspace technique. It is worth mentioning that, the distributed fault detection approach has the same performance as the centralized fault detection approach and avoids complex information exchange. In the end, a numerical simulation example and a case study of the three-phase flow facility are illustrated to show that the proposed distributed approach can accomplish the fault detection task successfully.
This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input *** propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the c...
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This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input *** propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the cost functions of a N-player Nash expert system given the expert's states and control *** allows us to address the imitation learning problem without prior knowledge of the expert's system *** achieve this,we provide a basic model-based algorithm that is built upon RL and inverse optimal *** serves as the foundation for our final model-free inverse RL algorithm which is implemented via neural network-based value function *** analysis and simulation examples verify the methods.
This work deals with the distributed attack-resilient consensus problem for continuous-time multi-agent systems on time-varying directed graphs. An unknown fraction of agents are Byzantine agents, which send false inf...
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Network systems refer to a new generation of systems with integrated information perception,transmission and utilization capabilities through communication networks,which are adopted to achieve desirable objectives un...
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Network systems refer to a new generation of systems with integrated information perception,transmission and utilization capabilities through communication networks,which are adopted to achieve desirable objectives under physical and information related uncertainties and/or adversary *** the information-rich era[1,2],one of the fundamental issues is to exploit the limit of feedback control on dissipating such uncertainties in the scenarios of networked sensing and communication[3].
Recently, some studies have shown that semantic and distortion representations both benefit the evaluation of image quality. However, the images of existing synthetic distortion databases are annotated with subjective...
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This paper discusses the implementation of time delays in ultra-high-speed applications. Sensorless controls are used to estimate the rotor speed and angle. In model-based sensorless control, the voltage and current s...
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We consider the control design of stochastic discrete-time linear multi-agent systems (MASs) under a global signal temporal logic (STL) specification to be satisfied at a predefined probability. By decomposing the dyn...
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