Due to the increasing penetration of distributed energy resources, congestion problems are already emerging in Dutch distribution grids. The available flexibility o f assets in the built environment could have the pot...
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Residential prosumers enable the peer-to-peer energy transfer to prompt the management of local energy resources for the benefit of their neighbourhood. This encourages the researchers to develop energy management pro...
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In this research, we propose a low-cost indoor localization technique using the CSI. By using CSI signal as input data, different locations and human activities are classified effectively using machine learning models...
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We introduce SetBERT, a fine-tuned BERT-based model designed to enhance query embeddings for set operations and Boolean logic queries, such as Intersection (AND), Difference (NOT), and Union (OR). SetBERT significantl...
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Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them h...
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Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.
Fire, as a type of disaster, poses a significant threat to both life and property safety. Therefore, timely and accurate detection of fire occurrences is of utmost importance. However, current fire detection methods t...
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Data science-based techniques have been widely applied in studies related to COVID-19 spread prediction. In these studies, different modeling techniques have been deployed to estimate the current and future trajectori...
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Cyber-physical power systems' reliance on cyberspace makes them vulnerable to cyber-attacks, particularly false data injection attacks (FDIAs), where the aim is to alter the state estimation (SE) results by changi...
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Aiming at the wind power prediction problem,a wind power probability prediction method based on the quantile regression of a dilated causal convolutional neural network is *** the developed model,the Adam stochastic g...
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Aiming at the wind power prediction problem,a wind power probability prediction method based on the quantile regression of a dilated causal convolutional neural network is *** the developed model,the Adam stochastic gradient descent technique is utilized to solve the cavity parameters of the causal convolutional neural network under different quantile conditions and obtain the probability density distribution of wind power at various times within the following 200 *** presented method can obtain more useful information than conventional point and interval ***,a prediction of the future complete probability distribution of wind power can be *** to the actual data forecast of wind power in the PJM network in the United States,the proposed probability density prediction approach can not only obtain more accurate point prediction results,it also obtains the complete probability density curve prediction results for wind *** with two other quantile regression methods,the developed technique can achieve a higher accuracy and smaller prediction interval range under the same confidence level.
We here present wafer-scale electrochromic films made of active plasmonic nano-chains. These plasmonic nanochains are readily fabricated via three simple steps, i.e. wafer-scale thin-film growth, thermal dewetting, an...
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