With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***...
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With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their *** address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree *** algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical *** our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical *** results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.
The detection of intermediate accounts in money laundering plays a crucial role in the process of anti-money laundering. Criminals are constantly developing new techniques to avoid detection, such as mixing money laun...
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Digital speech processing applications including automatic speech recognition (ASR), speaker recognition, speech translation, and others, essentially require large volumes of speech data for training and testing purpo...
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Edge computing fulfills the urgent need of users for low-latency and high-quality computing services by transferring tasks from end devices to the edge side of the network for processing through task offloading techni...
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Sentiment analysis can be used to identify if a text’s sentiment is neutral, positive, or negative. One type of natural language processing is sentiment analysis. An interdisciplinary field encompassing linguistics, ...
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Deploying service nodes hierarchically at the edge of the network can effectively improve the service quality of offloaded task requests and increase the utilization of *** this paper,we study the task scheduling prob...
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Deploying service nodes hierarchically at the edge of the network can effectively improve the service quality of offloaded task requests and increase the utilization of *** this paper,we study the task scheduling problem in the hierarchically deployed edge *** first formulate the minimization of the service time of scheduled tasks in edge cloud as a combinatorial optimization problem,blue and then prove the NP-hardness of the *** from the existing work that mostly designs heuristic approximation-based algorithms or policies to make scheduling decision,we propose a newly designed scheduling policy,named Joint Neural Network and Heuristic Scheduling(JNNHSP),which combines a neural network-based method with a heuristic based *** takes the Sequence-to-Sequence(Seq2Seq)model trained by Reinforcement Learning(RL)as the primary policy and adopts the heuristic algorithm as the auxiliary policy to obtain the scheduling solution,thereby achieving a good balance between the quality and the efficiency of the scheduling ***-depth experiments show that compared with a variety of related policies and optimization solvers,JNNHSP can achieve better performance in terms of scheduling error ratio,the degree to which the policy is affected by re-sources limitations,average service latency,and execution efficiency in a typical hierarchical edge cloud.
In order to improve the efficiency of signal control at regional intersections, aiming at the problems that the multi-agent reinforcement learning algorithm does not take into account the effect of the local Q value o...
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Owing to the phenomena of missed and false detections of floating bottles in river channels, and simultaneously, the large number of model parameters and high computational complexity, which is not conducive to end-to...
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In this study, the event-triggered asymptotic tracking control problem is considered for a class of nonholonomic systems in chained form for the time-varying reference input. First, to eliminate the ripple phenomenon ...
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In this study, the event-triggered asymptotic tracking control problem is considered for a class of nonholonomic systems in chained form for the time-varying reference input. First, to eliminate the ripple phenomenon caused by the imprecise compensation of the time-varying reference input, a novel time-varying event-triggered piecewise continuous control law and a triggering mechanism with a time-varying triggering function are developed. Second, an explicit integral input-to-state stable Lyapunov function is constructed for the time-varying closed-loop system regarding the sampling error as the external input. The origin of the closed-loop system is shown to be uniformly globally asymptotically stable for any global exponential decaying threshold signals, which in turn rules out the Zeno behavior. Moreover, infinitely fast sampling can be avoided by appropriately tuning the exponential convergence rate of the threshold signal. A numerical simulation example is provided to illustrate the proposed control approach.
In the current information society, the dissemination mechanisms and evolution laws of individual or collective opinions and their behaviors are the research hot topics in the field of opinion dynamics. First, in this...
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In the current information society, the dissemination mechanisms and evolution laws of individual or collective opinions and their behaviors are the research hot topics in the field of opinion dynamics. First, in this paper, a two-layer network consisting of an individual-opinion layer and a collective-opinion layer is constructed, and a dissemination model of opinions incorporating higher-order interactions(i.e. OIHOI dissemination model) is proposed. Furthermore, the dynamic equations of opinion dissemination for both individuals and groups are presented. Using Lyapunov's first method,two equilibrium points, including the negative consensus point and positive consensus point, and the dynamic equations obtained for opinion dissemination, are analyzed theoretically. In addition, for individual opinions and collective opinions,some conditions for reaching negative consensus and positive consensus as well as the theoretical expression for the dissemination threshold are put forward. Numerical simulations are carried to verify the feasibility and effectiveness of the proposed theoretical results, as well as the influence of the intra-structure, inter-connections, and higher-order interactions on the dissemination and evolution of individual opinions. The main results are as follows.(i) When the intra-structure of the collective-opinion layer meets certain characteristics, then a negative or positive consensus is easier to reach for individuals.(ii) Both negative consensus and positive consensus perform best in mixed type of inter-connections in the two-layer network.(iii) Higher-order interactions can quickly eliminate differences in individual opinions, thereby enabling individuals to reach consensus faster.
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