This study presents a novel approach for the adaptive control of chaotic spur gear systems using Proximal Policy Optimization (PPO) and attention-based learning. The spur gear system is known for its chaotic behavior,...
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Collaboration of agents in a natural swarm enables the accomplishment of tasks that would be difficult or impossible for a single agent to complete alone. For example, a swarm of autonomous Unmanned Aerial Vehicles (U...
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Achieving accurate electricity price prediction is essential for market participants aiming to maximize their profits. In this respect, forecasting wholesale electricity market price plays a pivotal role. The advanced...
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With the technical progress in the fields of robotics as well as artificial intelligence, many intelligent algorithms which focus on robot path planning problems have been developed so far. A∗ algorithm is an efficien...
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The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup offers the chance to deploy robots in ...
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Background: As the "three-type two-net, world-class" strategy is proposed, the key issues to be addressed are that the number of cloud resources in power grid continues to grow and there is a large amount of...
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With the recent focus marked on conversion efficiency and renewable energy, more research is being devoted to the high-performance maximum power point tracking technology for photovoltaic applications. However, the in...
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The vehicular edge computing(VEC)is a new paradigm that allows vehicles to offload computational tasks to base stations(BSs)with edge servers for *** general,the VEC paradigm uses the 5G for wireless communications,wh...
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The vehicular edge computing(VEC)is a new paradigm that allows vehicles to offload computational tasks to base stations(BSs)with edge servers for *** general,the VEC paradigm uses the 5G for wireless communications,where the massive multi-input multi-output(MIMO)technique will be ***,considering in the VEC environment with many vehicles,the energy consumption of BS may be very *** this paper,we study the energy optimization problem for the massive MIMO-based VEC *** at reducing the relevant BS energy consumption,we first propose a joint optimization problem of computation resource allocation,beam allocation and vehicle grouping *** the original problem is hard to be solved directly,we try to split the original problem into two subproblems and then design a heuristic algorithm to solve *** results show that our proposed algorithm efficiently reduces the BS energy consumption compared to other schemes.
The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy *** achieve safe management and optimal control of batteries,the state of charge(SOC...
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The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy *** achieve safe management and optimal control of batteries,the state of charge(SOC)is one of the important *** machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent ***,a common problem with these models is that their estimation performances are not always stable,which makes them difficult to use in practical *** address this problem,an optimized radial basis function neural network(RBF-NN)that combines the concepts of Golden Section Method(GSM)and Sparrow Search Algorithm(SSA)is proposed in this ***,GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model,and its parameters such as radial base center,connection weights and so on are optimized by SSA,which greatly improve the performance of RBF-NN in SOC *** the experiments,data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model,and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.
This paper proposes a consensus-based distributed algorithm to solve both active and reactive sharing problems, which involves alternative current (AC) microgrids and spatially concentrated dispatchable distributed ge...
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