With the rapid development of online education around world, it becomes difficult for teachers to evaluate the effect of learning during the online class. To solve this problem, an attention detection system based on ...
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Sample generation is an effective way to solve the problem of the insufficiency of training data for hyperspectral image classification. The generative adversarial network（GAN） is one of the popular deep learning me...
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Sample generation is an effective way to solve the problem of the insufficiency of training data for hyperspectral image classification. The generative adversarial network（GAN） is one of the popular deep learning methods, which utilizes adversarial training to generate the region of samples based on the required class label. In this paper, we propose cascade conditional generative adversarial nets for hyperspectral image complete spatial-spectral sample generation, named C;GAN. The C;GAN includes two stages. The stageone model consists of the spatial information generation with a window size that entails feeding random noise and the required class label. The second stage is the spatial-spectral information generation that generates spectral information of all bands in the spatial region by feeding the label regions. The visualization and verification of generated samples based on the Pavia University and Salinas datasets show superior performance, which demonstrates that our method is useful for hyperspectral image classification.
In deep geological drilling, encountering various formations is inevitable. Formation changes can lead to fluc-tuations in the weight on bit due to the bit-rock interaction. This paper proposes a disturbance observer-...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
In deep geological drilling, encountering various formations is inevitable. Formation changes can lead to fluc-tuations in the weight on bit due to the bit-rock interaction. This paper proposes a disturbance observer-based weight on bit control system to mitigate the adverse effects of formation changes on system performance. First, an axis-torsion coupled dynamic model is established, and the relationship between the two dimensions is analyzed. The validity of the model is confirmed through comparison with field data collected from a geothermal well drilling operation. Then, a disturbance observer is designed to estimate and compensate for the disturbance at the control input, thereby reducing weight on bit fluctuations caused by formation variations. Simulation results considering formation variation during drilling verify the effectiveness of the proposed method.
Three-dimensional trajectory planning is crucial for improving the safety and operational efficiency of unmanned aerial vehicle(UAV). However, it is hard to plan a suitable path in complex real-world environments. To ...
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Aiming at the truck scheduling problem in the open-pit mine scenario, a truck scheduling model based on real-time ore blending is established, and an adaptive evolution algorithm for truck scheduling based on DCNSGA-I...
Aiming at the truck scheduling problem in the open-pit mine scenario, a truck scheduling model based on real-time ore blending is established, and an adaptive evolution algorithm for truck scheduling based on DCNSGA-III is proposed. In the established scheduling model, the real-time grade variance of the crushing plant is minimized as one of the optimization objectives, and the Q-learning algorithm is introduced to adaptively select one of the most effective operators during the search process. Experiments show that the proposed method can effectively control the grade fluctuation of the ore flow and better scheduling schemes are obtained in comparison with algorithms equipped with the traditional search operator selection methods.
As a supporting technology in the field of human-computer interaction, speaker localization method has been a research hotspot in recent years. However, the existing single-mode speaker location methods cannot meet th...
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In recent years,cooperative coverage control of multi-agent system(MAS)has attracted plenty of researchers in various fields[1,2].Different from multi-agent consensus or synchronization,multi-agent coverage control ca...
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In recent years,cooperative coverage control of multi-agent system(MAS)has attracted plenty of researchers in various fields[1,2].Different from multi-agent consensus or synchronization,multi-agent coverage control cares about how to coordinate a team of agents for effectively monitoring or covering a given terrain,which inevitably gives rise to the interaction between individual dynamics and external ***,environmental uncertainties that include static uncertainties and dynamic uncertainties and limited sensing capabilities of a single agent make it a great challenge to design control algorithms of MAS for achieving the desired coverage performance.
Under an abnormal situation in process operations, it is important to find out the root cause, so as to bring the system back to normal timely. In a typical modern industrial facility, there are configured a large num...
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Convolutional Neural Networks (CNN) based Speech Emotion Recognition (SER) has the problem of learning bias towards stronger emotions while giving less weight to relatively faint emotions. This lack of subtleness caus...
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The performance of speech emotion recognition (SER) systems can be significantly compromised by the sentence structure of words being spoken. Since the relation between affective content and the lexical content of spe...
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