Electroencephalography (EEG) contains a wealth of information, including neuron activity, allowing for a partial understanding of the brain's state. As a reliable tool, EEG, combined with deep neural networks, has...
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We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the referen...
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In this paper, we present a model-free deep reinforcement learning (DRL) algorithm to control the locomotion of a quadruped robot adaptively at challenging terrain. This approach is used to improve the robot's abi...
Pseudo-LiDAR point clouds are generated from monocular *** with the point cloud from LiDAR,it can provide denser *** to the inaccuracy of depth estimation,there is still a performance gap between the pseudo-LiDAR poin...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Pseudo-LiDAR point clouds are generated from monocular *** with the point cloud from LiDAR,it can provide denser *** to the inaccuracy of depth estimation,there is still a performance gap between the pseudo-LiDAR point cloud and the LiDAR *** this paper,we propose an approach to eliminate the performance degradation caused by deviation of depth estimation and realize 3 D object detection based on pseudo-LiDAR point *** results on KITTI 3 D benchmark illustrate that in contrast to other methods,our scheme can achieve more reliable performance on both object localization and shape estimation.
Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide *** emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simulation,opt...
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Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide *** emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simulation,optimization and assessment for a novel NH_(3)deep purification process using *** process was designed and investigated by simulation and optimization using ionic liquid[C_(4)im][NTF_(2)]as *** objective functions,total purification cost(TPC),total process CO_(2)emission(TPCOE)and thermal efficiency(ηeff)were employed to optimize the absorption *** simulation and optimization results indicate that at same purification standard and recovery rate,the novel process can achieve lower cost and CO_(2)emission compared to benchmark *** process optimization,the optimal functions can achieve 0.02726$/Nm~3(TPC),311.27 kg CO_(2)/hr(TP-COE),and 52.21%(ηeff)for enhanced ***,compared with conventional process,novel process could decrease over$3 million of purification cost and 10000 tons of CO_(2)emission during the life *** results provide a novel strategy and guidance for deep purification of NH_(3)capture.
Oil-gas-water three-phase flow process is a dynamic non-stationary system,and the flow states are extremely complicated due to the three-phase *** at state identification of water-based dispersed three-phase flow,a st...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Oil-gas-water three-phase flow process is a dynamic non-stationary system,and the flow states are extremely complicated due to the three-phase *** at state identification of water-based dispersed three-phase flow,a strategy combining locality preserving projections(LPP) and Gaussian-weighted k-nearest neighbor(GWKNN) is *** on statistics pattern analysis(SPA),rich state information can be *** constructing the combined model of LPP and GWKNN,the local neighborhood structures are preserved and the local characteristics of flow states are *** effectiveness of the strategy is demonstrated by experiments.
In this paper,we study the energy scheduling problem of solar-powered aircraft microgrid with multi-agent deep reinforcement learning algorithm under a centralized training and decentralized execution *** problem is m...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,we study the energy scheduling problem of solar-powered aircraft microgrid with multi-agent deep reinforcement learning algorithm under a centralized training and decentralized execution *** problem is modeled as a multi-agent Markov decision process and embedded in a multi-agent proximal policy optimization framework.A scheduling policy is proposed by offline training and then utilized for online ***,two forms of action spaces are constructed to explore a more favorable *** experiments show that the algorithm enables us to obtain an effective policy in solving the energy scheduling problem.
It is difficult to accurately measure the flow parameters of gas-liquid two-phase flow in horizontal pipe because of its complexity and *** of two-phase flow pattern is helpful to analyze fluid flow state and provide ...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
It is difficult to accurately measure the flow parameters of gas-liquid two-phase flow in horizontal pipe because of its complexity and *** of two-phase flow pattern is helpful to analyze fluid flow state and provide more information for accurate measurement of flow *** this paper,a two-phase flow pattern diagnosis algorithm based on acoustic-electrical data fusion is ***,chaos recursive analysis is performed on the data obtained by electronic resistance tomography(ERT) *** wavelet transform is performed on ERT data and the total energy of wavelet transform is ***,spectrum analysis is used on the ultrasonic Doppler data,and statistical characteristics of spectrum bandwidth and average velocity are *** vector machine(SVM) and K-nearest neighbor were used to distinguish these features objectively,and the recognition accuracy are 88% and 92%.
This paper investigates the consensus of one-sided Lipschitz(OSL) multi-agent systems(MASs) in the presence of input saturation and external disturbance over directed communication topology.A saturation avoidance stra...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
This paper investigates the consensus of one-sided Lipschitz(OSL) multi-agent systems(MASs) in the presence of input saturation and external disturbance over directed communication topology.A saturation avoidance strategy is suggested to handle the input *** enables us to deal with both open-loop stable and open-loop unstable *** employing the Lyapunov theory,the consensus problem is changed into the stabilization one through the error *** design a control protocol and convert the problems of disturbance rejection and domain of attraction into the optimization of two invariant ***,some numerical simulations are given to verify the effectiveness of the proposed consensus protocol.
Gas-water two-phase flow process is complex and ***-time monitoring of flow status evolution is helpful to the safe *** progress of multi-sensor technology makes it possible to accurately measure the flow information,...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Gas-water two-phase flow process is complex and ***-time monitoring of flow status evolution is helpful to the safe *** progress of multi-sensor technology makes it possible to accurately measure the flow information,which lays a data foundation for the establishment of flow status monitoring *** to the instability and randomness of flow,there are both nonstationary and stationary signals in the measurement *** this paper,the augmented Dickey Fuller(ADF) test is used to distinguish nonstationary signals from stationary *** analysis(CA) can deal with the problem that the fluctuation of nonstationary signals masks the change trend of flow *** stationary signals,kernel canonical variate analysis(KCVA) is used to realize the nonlinear mapping and obtain the canonical features reflecting the dynamic *** monitoring indexes are built and combined to monitor the flow ***-KCVA method is applied to the data of gas-water two-phase flow in horizontal *** monitoring results prove the effectiveness.
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