In order to improve the braking effect of electric vehicles, multi-objective optimization, and fuzzy control decision-making are used to distribute the braking torque. The Pareto solution set is constructed by multi-o...
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Time series clustering algorithm of a change in process parameters based on statistical homogeneity of time series fragment of a single cluster is suggested in the article. The selected clusters characterize stationar...
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This paper focuses on modeling and analyzing an orbit determination technique specifically tailored to geostationary satellites employing active maneuvers. Active maneuvers involving deliberate orbital adjustments, us...
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To address the problem of data deficiency in bridge monitoring data, this paper combines the extreme gradient boosting algorithm XGBoost with Transformer network based on Transformer network in the context of Meixi Ri...
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ISBN:
(纸本)9798350334722
To address the problem of data deficiency in bridge monitoring data, this paper combines the extreme gradient boosting algorithm XGBoost with Transformer network based on Transformer network in the context of Meixi River Bridge, constructs a combined XGBoost-Transformer model, and discusses its application characteristics, analysisprocess and modelingprocess. The analysis of the experimental results reveals that the prediction data of the XGBoost-Transformer model achieves an accuracy of 93.0% with a confidence interval of +/- 0.15 mm. Compared with the Transformer model, the XGBoost-Transformer model has higher prediction accuracy and lower RMSE and MAE of 0.1014 and 0.0756, respectively, practice shows that the fusion of the time-series database InfluxDB with the XGBoost-Transformer model effectively recovers the missing bridge deflection data, increasing the utilization and analyzability of bridge deflection data.
Nitrogen gas under pressure released from storage is expected to flow at a set pressure at the downstream end of the control valve. The dynamic changes in pressure and temperature are measured and the Proportional- In...
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In the field of engineering, Finite Element analysis (FEA) serves as a pivotal numerical simulation tool. Nevertheless, its inherent offline nature and dependency on real-time data pose limitations on its versatility....
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The limit behavior of a semi-Markov process, depending on a small parameter, is important for the analysis and optimization of telecommunication systems. Semi-Markov processes are an extension of Markov processes that...
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A smart data holistic approach for context-aware data analytics (AETHER-UA) is one of the four sub-projects, developed in the University of Alicante, being part of the whole project AETHER. This project is being devel...
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Next-generation manufacturing involves increasing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processe...
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ISBN:
(数字)9781665451963
ISBN:
(纸本)9781665451963
Next-generation manufacturing involves increasing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processes) and new data modalities (e.g., images) are integrated with traditional plant automation concepts, will be how to best evaluate alternative strategies for data-driven modeling and synthesizing processdata. Two methods which could be used to aid in this are those which aid in testing data-based techniques on-line, and those which enable various data-based techniques to be assessed in simulation. In this work, we discuss two techniques in this domain which can be applied in the context of chemical processcontrol, along with their benefits and limitations. The first is a method for testing data-driven modeling strategies on-line by postulating the experimental conditions which could reveal if a model is correct, and then attempting to collect data which could help to reveal this. The second strategy is a framework for testing image-based control algorithms via simulating both the generation of the images as well as the impacts of control on the resulting systems.
The presented paper is concerned with the capabilities of 3D geospatial technologies in the decision-support process for the design, construction, and employment of engineering structures. Among the various geospatial...
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The presented paper is concerned with the capabilities of 3D geospatial technologies in the decision-support process for the design, construction, and employment of engineering structures. Among the various geospatial technologies, the primary stress is made on terrestrial laser scanning (TLS). Despite the widespread application of TLS, its opportunities are not studied thoroughly. A vast volume of studies is dedicated to accuracy, processing workflow, and modeling by TLS data. However, only scanty research considers the TLS technology and data from an ordinary civil engineer's point of view. This study attempts to fill this gap. Covered topics are analysis of the current trends of measurement technologies;in-depth analysis of laser scanning results as a source of new unique data;laser scanning for industrial applications;laser scanning and BIM integration. Except for the mentioned topics, the new concept of the complete control of geometric parameters during the construction and operation of engineering structures is introduced. Complete control plays an indispensable role in the decision-support process during the building life cycle and therefore is an inherent part of any BIM. A description of the steps of complete control and its different applications for civil engineering is given. The decisionsupport process is addressed for different structures, e.g., roads, civil and industrial structures, oil and gas industry objects, etc. Moreover, complete control is considered for the various stages of a building life cycle, from design to demolition. The results provide convincing evidence that the complete control by TLS data has a prominent role in the decision-support process for civil engineering.
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