The convergence of flying objects, Mobile Ad Hoc Networks (MANETs), and Wireless Sensor Networks (WSNs) has been made feasible by the widespread proliferation of wireless communication technology. This study delves in...
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With the increasing integration of power plants into the frequency-regulation markets, the importance of optimal trading has grown substantially. This paper conducts an in-depth analysis of their optimal trading behav...
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In the digital age, the agricultural industry faces unique challenges, including the efficient management and maintenance of farm vehicles and tools. This paper introduces a blockchain-based agricultural vehicle and t...
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Exploration strategy design is a challenging problem in reinforcement learning(RL),especially when the environment contains a large state space or sparse *** exploration,the agent tries to discover unexplored(novel)ar...
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Exploration strategy design is a challenging problem in reinforcement learning(RL),especially when the environment contains a large state space or sparse *** exploration,the agent tries to discover unexplored(novel)areas or high reward(quality)*** existing methods perform exploration by only utilizing the novelty of *** novelty and quality in the neighboring area of the current state have not been well utilized to simultaneously guide the agent’s *** address this problem,this paper proposes a novel RL framework,called clustered reinforcement learning(CRL),for efficient exploration in *** adopts clustering to divide the collected states into several clusters,based on which a bonus reward reflecting both novelty and quality in the neighboring area(cluster)of the current state is given to the *** leverages these bonus rewards to guide the agent to perform efficient ***,CRL can be combined with existing exploration strategies to improve their performance,as the bonus rewards employed by these existing exploration strategies solely capture the novelty of *** on four continuous control tasks and six hard-exploration Atari-2600 games show that our method can outperform other state-of-the-art methods to achieve the best performance.
To enable message transmission among sensors and equipment,power line communication(PLC)is a widely adopted smart ***,due to the occurrence of impulsive noise(IN),reliable transmissions over PLC channels in the smart ...
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To enable message transmission among sensors and equipment,power line communication(PLC)is a widely adopted smart ***,due to the occurrence of impulsive noise(IN),reliable transmissions over PLC channels in the smart grid are ***,in this paper,we propose an adaptive noise mitigation scheme to clip the IN with the sliding window-based method,where the altitude of the received signal in the current time slots is obtained by computing the average altitude of signals in the previous and next time *** detect the states of IN and dynamically estimate the power threshold of signals for the IN mitigation scheme,we develop an intelligent algorithm based on the long short-term memory *** prevent the useful signals from being eliminated as IN signals,we propose the accelerated proximal gradient method(APGM)based on tone reservation to reduce the peak-to-average power ratio(PAPR)for the transmitting signals with low computational *** addition,the closed-form expression of the bit error rate(BER)is derived for the proposed sliding window-based IN mitigation scheme according to the probability density function of the *** results demonstrate that the proposed IN mitigation scheme achieves a better BER performance than the conventional IN mitigation *** addition,the APGM aided by IN mitigation can further improve BER performance due to the PAPR reduction.
In the field of adversarial games, existing decision-making algorithms primarily rely on reinforcement learning, which can theoretically adapt to diverse scenarios through trial and error. However, these algorithms of...
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Machining centers (MCs) are crucial high-technology machine tools that are widely used in the manufacturing industry. Since their high investment necessities, the selection of the appropriate MC for a company is an im...
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作者：
Sim, SeungminKim, JinwoongLee, Jemin
Department of Electrical and Computer Engineering Korea Republic of
Department of Electrical Engineering and Computer Science Korea Republic of
In this paper, we analyze covert amplify-and-forward (AF) relay networks with a metric for measuring the data freshness, i.e, age of information (AoI), with aid of the cooperative jammer that generates artificial nois...
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This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from ...
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This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.
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