Predicting traffic flow is important for improving safety and efficiency in IoV systems. Techniques such as traditional models, deep learning, hybrid approaches, graph-based methods, optimization, edge computing, and ...
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The present study focuses on the iterative learning control to switched nonlinear systems incorporating time-varying delay. Initially, the system is reformulated as a nonlinear switched continuous-discrete two-dimensi...
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With the continuous expansion of the power system scale and the continuous development of the power network, the traditional power system management and optimization methods face many challenges. In order to meet the ...
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With the continuous expansion of the power system scale and the continuous development of the power network, the traditional power system management and optimization methods face many challenges. In order to meet the requirements of voltage optimization and adjustment, the optimization problem is divided into cloud front precomputation and edge computing device cooperative optimization computation with the framework of cloudedge cooperation. The cloud front-end precomputation uses an improved reactive-voltage sensitivity based on an improved modularity function to partition the power system on a 15 min basis and stores the results in the cloud data memory. The voltage threshold device detects the node voltage overrun and triggers the collaborative optimization computation of the edge computing devices, which sends a command to the cloud to call the partitioning result of this time period, and the cloud sends the result to each edge computing device, which determines the area it is responsible for, and adjusts the voltage overrun partitioning by using the mixed-integer second-order conic planning, and ultimately realizes the optimization strategy within the minute-level zone. Since the voltage adjustment is a fine-grained optimization of the local area, it is highly flexible and targeted. Moreover, using the cloud-edge collaboration technology, the intelligent management and optimization of the power system is finally realized. Case analysis and comparative verification show that the method proposed in this paper is accurate and highly efficient.
To enhance the contour accuracy of biaxial systems, this paper proposes a compensation method that models independent single-axis systems and then couples multiple servo axes through model predictive control algorithm...
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Nowadays, cloud storage is one of the popular application models in various fields, where the security and access permission of storage data are widely considered. De-duplication algorithms are designed to mitigate re...
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Visible Light Communication (VLC) is a growing trend in future communication technology. In VLC systems, Free Space Optics (FSO) is used as the transmission medium. These VLC FSO systems offer solutions to congestion ...
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作者：
Soma, Arun KumarPark University
Department of Information Systems & Business Analytics 8700 NW River Park Dr ParkvilleMO64152 United States
Graph data analysis benefits from detecting substructures to infer meaning and interpret data correctly. However, many existing graph clustering algorithms are not applicable to weighted graphs, which contain edge wei...
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The increasing complexity of modern plant systems and the limitations of precise mathematical modeling have led to a shift towards data-driven control methods. These methods present an effective alternative that treat...
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This paper presents a comprehensive approach to controlling a Parrot Mambo minidrone in a simulation environment using MATLAB. The primary objective is to guide the drone along a predefined path while maintaining stab...
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作者：
Soma, Arun KumarPark University
Department of Information Systems & Business Analytics 8700 NW River Park Dr ParkvilleMO64152 United States
The Aether sensor network is a system of sensors that are used to monitor the environment and detect changes in the atmosphere. It is a system of sensors that are used to monitor the environment and detect changes in ...
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