Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-...
详细信息
Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.
This paper introduces a learning-based optimal control strategy enhanced with nonmodel-based state estimation to manage the complexities of lane-changing maneuvers in autonomous vehicles. Traditional approaches often ...
详细信息
Traditional transient angle stability analysis methods do not fully consider the spatial characteristics of the network topology and the temporal characteristics of the time-series ***,a data-driven method is proposed...
详细信息
Traditional transient angle stability analysis methods do not fully consider the spatial characteristics of the network topology and the temporal characteristics of the time-series ***,a data-driven method is proposed in this study,combining graph convolution network and long short-term memory network(GCN-LSTM)to analyze the transient power angle sta-bility by exploring the spatiotemporal disturbance char-acteristics of future power systems with high penetration of renewable energy sources(wind and solar energy)and power *** key time-series electrical state quantities are considered as the initial input feature quantities and normalized using the Z-score,whereas the network adjacency matrix is constructed according to the system network *** normalized feature quan-tities and network adjacency matrix were used as the inputs of the GCN to obtain the spatial features,reflecting changes in the network ***,the spa-tial features are inputted into the LSTM network to ob-tain the temporal features,reflecting dynamic changes in the transient power angle of the ***,the spatiotemporal features are fused through a fully con-nected network to analyze the transient power angle stability of future power systems,and the softmax activa-tion cross-entropy loss functions are used to predict the stability of the *** proposed transient power angle stability assessment method is tested on a 500 kV AC-DC practical power system,and the simulation results show that the proposed method could effectively mine the spatiotemporal disturbance characteristics of power sys-tems. Moreover, the proposed model has higher accuracy, higher recall rate, and shorter training and testing times than traditional transient power angle stability algo-rithms.
The identification capacity region of the compound broadcast channel is determined under an average error criterion, where the sender has no channel state information. We give single-letter identification capacity for...
详细信息
In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the curr...
详细信息
In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.
Traditional lithography techniques are currently facing challenges, including high costs and the susceptibility of mask plates to damage. This research aims to elucidate the feasibility and technical constraints of a ...
详细信息
While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector spaces endowed with non-Euclidean norms, s...
详细信息
While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector spaces endowed with non-Euclidean norms, such as diagonally-weighted ℓ1 or ℓ1 norms. This paper provides a natural generalization of monotone operator theory to finitedimensional non-Euclidean spaces. The key tools are weak pairings and logarithmic norms. We show that the resolvent and reected resolvent operators of non-Euclidean monotone mappings exhibit similar properties to their counterparts in Hilbert spaces. Furthermore, classical iterative methods and splitting methods for finding zeros of monotone operators are shown to converge in the non-Euclidean case. We apply our theory to equilibrium computation and Lipschitz constant estimation of recurrent neural networks, obtaining novel iterations and tighter upper bounds via forward-backward splitting.
This paper proposes a comprehensive methodology for Field-Oriented control (FOC) with parameter variation analysis for Interior Permanent Magnet Synchronous Machines (IPMSM). The modeling approach for an IPMSM is firs...
详细信息
This paper proposes a comprehensive methodology for Field-Oriented control (FOC) with parameter variation analysis for Interior Permanent Magnet Synchronous Machines (IPMSM). The modeling approach for an IPMSM is first presented, followed by a step-by-step procedure for designing a vector-controlled strategy. The formulation is based on a dq-rotating reference frame aligned with the rotor shaft position. A key distinction of this methodology from traditional approaches is that the current controller is designed in the time domain based on desired time constants, while the speed control is formulated within a frequency response domain framework. The proposed hybrid approach enables accurate tuning of the Proportional-Integrator (PI) controllers for both current and speed control loops. Additionally, a parameter variation analysis is conducted to enhance the proposed methodology. The validity region for the design procedure is presented, ensuring that for any wide speed variation of the machine, loop gains are properly tuned. One of the main advantages of the proposed methodology is that it provides a fast, reliable, and accurate technique for implementing IPMSM drive systems. Results from a controller Hardware-in-the-Loop (C-HIL) setup with an external microcontroller are presented. The comprehensive design approach is validated under two different IPMSM parameter sets, demonstrating its effectiveness.
This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell...
详细信息
The economic dispatch problem (EDP) poses a significant challenge in energy management for modern power systems, particularly as these systems undergo expansion. This growth escalates the demand for communication reso...
详细信息
暂无评论