In recent years, unmanned aerial vehicle (UAV) technology has developed rapidly, which plays an important role in both military and civil fields. While it brings convenience to all walks of life, there are also a lot ...
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This paper investigates the cooperative guidance issue for multiple unmanned aerial vehicles (UAVs) for simultaneous attacks on maneuvering targets with a prescribed angle formation. Each UAV is accessible to the rela...
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Identifying influential nodes is a recognized challenge for the tremendous number of nodes in complex networks. Most of proposed methods detect the influential nodes based on their degree or topological location, whic...
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The accurate prediction of remaining useful life (RUL) is vital to improve the safety and reliability of lithium-ion battery power systems. However, owing to the effects of state (work and storage) switching and reten...
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A simulation model of a simple supply chain consisting of a single distribution center and several points of sale was created. Initially, a new model was created with the name "Suplly Chain"and watches as un...
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How improve the mapping efficiency and location accuracy of the multi-UAV cluster based on the distributed SLAM technology is a significant problem in overlapping regions. Therefore, this paper mainly proposes a novel...
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Focused on revising the cumulative error of the SINS, a dual-mode navigation algorithm based on the infrared and SAR information fusion is studied in this paper. The SAR system can provide the SAR image and the inform...
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In order to scientifically and effectively evaluate the performance indexes of aircraft, the common Bayes multi-source data fusion method can comprehensively utilize a variety of information types under the condition ...
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ISBN:
(数字)9798350389463
ISBN:
(纸本)9798350389470
In order to scientifically and effectively evaluate the performance indexes of aircraft, the common Bayes multi-source data fusion method can comprehensively utilize a variety of information types under the condition that the decision risk is as small as possible, but there are risks such as insufficient data utilization and small sample data being “submerged” by large sample data in the fusion. This paper proposes a test data expansion method based on the combination of probability features and BP neural network model, and is verified by typical application to ensure that the sample size of multi-source data is comparable. Supplementary data not only retains the probability features of the original data, but also the sample generation has physical connotation.
A magneto-quasi-static (MQS) surface integral equation (SIE) formulation with loop analysis is proposed to extract the impedance of interconnects in packages. The loop analysis is developed with an independent and com...
A magneto-quasi-static (MQS) surface integral equation (SIE) formulation with loop analysis is proposed to extract the impedance of interconnects in packages. The loop analysis is developed with an independent and complete set of unknowns according to the graph theory, which can significantly reduce the dimension of the final matrix. With the pre-corrected fast Fourier Transform (pFFT), large-scale interconnects can be efficiently modelled. A practical example in packages is carried out to validate the effectiveness and scalability of the proposed formulation. Results show that the proposed formulation is accurate and flexible to model complex interconnects in packages compared with the industrial solver.
Fault influence and propagation analysis of flight vehicle systems is an important element of flight vehicle health management and also an important problem to be solved. A fault influence model based on data-driven i...
Fault influence and propagation analysis of flight vehicle systems is an important element of flight vehicle health management and also an important problem to be solved. A fault influence model based on data-driven is established, including a prediction model of flight parameters under fault, a dynamic influence path, and an influence degree model. Based on the historical experimental data, a long and short-term memory neural network (LSTM) model is proposed to predict the time-series data of each flight parameter of the flight vehicle under fault; based on the prediction results, a symbolic directed graph (SDG) is used to describe the fault of the flight vehicle system, and then introduce the concept of a compatible path with time-series characteristics to describe the dynamic propagation process of the fault. The case shows that the method proposed in this paper enables qualitative and quantitative analysis of the fault influence, and can reasonably describe the fault propagation path and influence characteristics.
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