In order to improve the performance of traditional SOM model, an adaptive SOM neural network algorithm is proposed. By introducing the error square sum solution formula, the clustering error of the model sub-data set ...
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Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization sched...
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In this paper, based on the condition that the inertial navigation system loaded on the aircraft has giant dispersion, and the aircraft need to detect, track and attack a target, thus the relative position relation ne...
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Condition monitoring of railway point machines is important for train operation safety and *** to the fields of mechanical equipment fault detection,this paper proposes a fault detection and identification strategy of...
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Condition monitoring of railway point machines is important for train operation safety and *** to the fields of mechanical equipment fault detection,this paper proposes a fault detection and identification strategy of railway point machines via vibration signals.A comprehensive feature distilling approach by combining variational mode decomposition(VMD)energy entropy and time-and frequency-domain statistical features is presented,which is more effective than single type of *** optimal set of features was selected with ReliefF,which helps improve the diagnosis *** vector machine(SVM),which is suitable for a small sample,is adopted to realize *** diagnosis accuracy of the proposed method reaches 100%,and its effectiveness is verified by experiment *** this paper,vibration signals are creatively adopted for fault diagnosis of railway point *** presented method can help guide field maintenance staff and also provide reference for fault diagnosis of other equipment.
In this paper,the problem of training a recurrent neural network(RNN) controller to approximate an active disturbance rejection control(ADRC) is *** learning methods,online learning and offline learning,are *** the on...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,the problem of training a recurrent neural network(RNN) controller to approximate an active disturbance rejection control(ADRC) is *** learning methods,online learning and offline learning,are *** the online setting,the RNN learning controller is trained by the error of the control quantity compared to that of ADRC in real time,while for the offline setting,the RNN controller is trained by the error of the whole state trajectory compared to that of ADRC obtained in *** randomized weight initialization,success rates of trained online and offline RNN learning controllers are compared by ***,the robustness property of the trained RNN controller is analyzed.A metric of robustness,which can be calculated from the weights of the trained RNN controller is also proposed.
The cooperative search strategy is designed with the distributed model predictive method in this paper. For the rationality of decision-making of UAV swarm in different stages of the cooperative search, a dynamic para...
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New requirements for coordinated aircraft attacks have been introduced with the development of the anti-missile systems. To address the problem of multi-flight collaborative strike, this paper proposes a distributed c...
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The Automotive Headlamp Leveling system (ALS), aims to ensure the stability of the illumination range of the headlamp by vertically rotate the headlamp using motors when the body attitude changes. This paper proposes ...
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Marine ship recognition has always been an important research field. The ships can be usually recognized by analyzing their attribute characteristics. However, in the actual process of recognition, many ship recogniti...
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In the field of electric vehicles, the safety of power lithium-ion batteries is a socially important issue, and the study of thermal runaway of lithium batteries is now gradually becoming more in-depth. In this paper,...
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