As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system sc...
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As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.
Aqueous zinc ion batteries（AZIBs） have excellent development prospects due to their high theoretical capacity and low ***,the commercial separator represented by glass fiber（GF） in AZIBs usually exhibits uneven po...
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Aqueous zinc ion batteries（AZIBs） have excellent development prospects due to their high theoretical capacity and low ***,the commercial separator represented by glass fiber（GF） in AZIBs usually exhibits uneven porosity,poor zincophilicity,and insufficient functional groups,resulting in the emergence of the zinc anode dendrites and side *** a separator with specific interfacial ion transport behavior is essential to achieve a highly stable reversible zinc ***,an anionic metal-organic framework（MOF） functionalized separator（GF-Bio-MOF-100） was presented to accelerate the desolvation process and modulate Zn2+flux,thereby delivering the decreased nucleation overpotential and uniform Zn2+*** in-depth kinetics investigations combined with the in-situ Raman spectroscopy demonstrate that the carbonyl group within the Bio-MOF-100 is capable of capturing the H2O molecules of [Zn（H2O）6]2+via the H-bond interaction,which further accelerates the desolvation process and transport kinetics of Zn2+.Meanwhile,the anionic framework of the GFBio-MOF-100 separator acts as an interfacial ion channel to regulate the Zn2+flux and enables dendrite-free Zn2+deposition and ***,the Zn|GF-Bio-MOF-100|Zn symmetric cell exhibited a stable Zn2+plating/stripping behavior and it could cycle for 2000 h at 0.3 mA ***,the assembled Zn|GF-Bio-MOF-100|MnO2full cell delivers a capacity retention of 83.9%after 1000 cycles at 0.5 A *** work provides new insights into the design of functionalized separators for long-life AZIBs.
With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicat...
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With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicated on 2D compressed sensing(CS)and the hyperchaotic ***,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong ***,the processed images are con-currently encrypted and compressed using 2D *** them,chaotic sequences replace traditional random measurement matrices to increase the system’s ***,the processed images are re-encrypted using a combination of permutation and diffusion *** addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct *** with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational ***,it has better *** experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.
Person Re-Identification falls within the scope of computer vision, acting a technique to ascertain the presence of a specified pedestrian within a video or image library. The related research is of great significance...
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In Currently, research in the field of infrared road object detection is primarily focused on enhancing model performance and robustness to address the challenges posed by complex real-world driving scenarios. In resp...
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Pedestrian re-identification technology enables accurate identification of individuals and is widely used in modern intelligent video surveillance systems to aid law enforcement, including criminal apprehension and lo...
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Underwater target detection is an important part of marine exploration. However, in complex underwater environments due to factors like light absorption and scattering, as well as variations in water quality and clari...
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In recent years, the utilization of unmanned aerial vehicles (UAVs) for aerial target detection has gained significant attention due to their high-altitude perspective and maneuverability, which offer novel opportunit...
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Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent syst...
Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent systems with bandit feedback is to explore and understand the equilibrium state to ensure stable and tractable system performance.
As deep learning advances, neural network technologies are increasingly penetrating the field of steel surface defect detection. To tackle the challenges of low accuracy and inadequate quality, we introduce CMS-YOLOv8...
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