Advanced knowledge engineering (KE), represented by knowledge graph (KG), drives the development of various fields and engineering technologies and provides various knowledge fusion and knowledge empowerment interface...
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Advanced knowledge engineering (KE), represented by knowledge graph (KG), drives the development of various fields and engineering technologies and provides various knowledge fusion and knowledge empowerment interfaces. At the same time, advanced system engineering (SE) takes model-based system engineering (MBSE) as the core to realize formal modeling and processanalysis of the whole system. The two complement each other and are the key technologies for the transition from 2.0 to 3.0 in the era of artificial intelligence and the transition from perceptual intelligence to cognitive intelligence. This survey summarizes an advanced information fusion system, from model-driven to knowledge-enabled. Firstly, the concept, representative methods, key technologies and application fields of model-driven system engineering are introduced. Then, it introduces the concept of knowledge-driven knowledge engineering, summarizes the architecture and construction methods of advanced knowledge engineering and summarizes the application fields. Finally, the combination of advanced information fusion systems, development opportunities and challenges are discussed.
The relevance of electronic testing in comparison with other forms of control and assessment of the mastery of the material covered in the discipline is considered. An analysis was carried out of 6 popular services fo...
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With the continuous increase of offshore wind farms and other offshore regional buildings, the contradiction between them and the navigation safety in the densely distributed areas of offshore ship tracks is increasin...
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With the continuous increase of offshore wind farms and other offshore regional buildings, the contradiction between them and the navigation safety in the densely distributed areas of offshore ship tracks is increasingly obvious. It is urgent to build a safe distance model based on the actual sea condition to reduce the mutual influence. Based on the drift distance of ships in the boundary water areas of the wind farm under the actual meteorological and hydrological conditions, as well as the tolerable collision probability, reliability model and the normal distribution trend of ships in the ship routes, and the probability model of safe distance between ship routes and wind farm is built in the end. Based on the example and the tolerable collision probability of ships, the safe distance is analyzed, the analysis results show that the calculation model can determine the safe distance according to the control requirements of the collision probability between the ship and the offshore wind farm. In addition, the collision probability and the safe distance obtained are basically consistent with the safe distance published by the local maritime authority in combination with the changes of the output results caused by the velocity difference of the ship. The model lays a theoretical foundation on offshore wind farm site selection optimization, route boundary demarcation, ship safety and maritime supervision.
The exergy analysis method is an important method for evaluating energy levels and energy efficiency. It is of great importance in the direction of process energy efficiency optimization. In this paper, the energy use...
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Nowadays, the utilization of online auction platforms is becoming increasingly prevalent. Online auction provides a common and practical way for global buyers to compete fairly. Nevertheless, the anonymous environment...
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This paper addresses the control-theoretic approach of an autonomous fog computing platform to process the of-ftoaded mobile robot vision data for warehouse applications. The approach entails polytopic linear paramete...
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ISBN:
(数字)9798350340266
ISBN:
(纸本)9798350340273
This paper addresses the control-theoretic approach of an autonomous fog computing platform to process the of-ftoaded mobile robot vision data for warehouse applications. The approach entails polytopic linear parameter varying (PLPV) modelling of the fog platform and the design of an event-triggered control to process the vision data within a specified time frame called service time, by auto-scaling the computing nodes. The PLPV model is developed using dynamic mobile robot vision data with image resolution and frame rate as parameters. The developed theory is experimentally validated on a mobile robot that navigates in a warehouse application environment, and the results are presented to show the efficacy of the proposed controller in meeting the service time requirements.
Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time (DT) models. However, even with nume...
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This paper presents a learning -based disturbance rejection control strategy for Urban Air Mobility (UAM) with vertical take -off and landing capability, which is subject to uncertainties in system parameters. The two...
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This paper presents a learning -based disturbance rejection control strategy for Urban Air Mobility (UAM) with vertical take -off and landing capability, which is subject to uncertainties in system parameters. The two primary sources of uncertainty during UAM operation, specifically moment of inertia uncertainty and center of gravity variation, are thoroughly analyzed as they negatively impact control performance. Building upon the analysis outcomes, a novel adaptive scheme is proposed that employs the modeling capabilities of Gaussian process regression for online learning to estimate model uncertainties. To ensure the collection of high -quality training data without relying on state derivatives, a nonlinear disturbance observer is employed as an artificial sensor. The suggested control algorithm is formulated by integrating Gaussian process regression with a baseline control derived using the feedback linearization control technique. Theoretical analysis grounded in the Lyapunov theorem reveals that the tracking error of the closed -loop system is semi -globally uniformly and ultimately bounded. Numerical simulations are conducted to validate the effectiveness of the proposed approach. The results obtained confirm that the proposed method can achieve superior tracking performance, even in the presence of model uncertainties and time -varying disturbances, surpassing existing approaches.
The increased need for accurately modeling the input-output characteristics of linear time-periodic (LTP) systems necessitates novel identification and control algorithms as well as new test benches for their experime...
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The increasing competition in the banking industry has made customer churn analysis and prediction a crucial concern. Banks must now adopt customer retention strategies while also working towards acquiring new custome...
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